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anagogic-transformation.txt
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C:\> for file in *.txt; do
> echo "Checking $file";
> ollama run mistral "Summarize:" < "$file";
> done
Checking #UiPathForward Americas 2017 Keynote Presentations.txt
The report discusses the current and future state of Robotic Process
Automation (RPA) and Artificial Intelligence (AI). It highlights that RPA will
continue to climb the cognitive scale, moving from rule-based to machine
learning capabilities. The report also mentions five emerging use cases for AI
with RPA support:
1. Chatbots for customer self-service
2. Chatbots for internal employees
3. Unstructured content analysis using text analytics
4. IoT sensors with predictive analytics
5. Data pooling and reporting with analytics
The report suggests that the future of RPA will emphasize human/machine
collaboration through cubicle process augmentation, where AI-powered digital
workers will assist employees in completing tasks. The report was published by
Forrester in 2018.
Checking 00-Scholl-Tremoulet-TICS.txt
The article by Isles and Wilkinson provides an overview of the concept of
genomic imprinting, which involves the silencing of one allele according to its
parental origin. This results in traits being passed down either the maternal
or paternal line. The authors argue that this type of inheritance is driven by
evolutionary conflict between the sexes. They review recent findings on the
effects of imprinted genes on behavioral and cognitive phenotypes, focusing on
mental disorders, Turner’s syndrome, and experimental work in animal models.
The authors suggest that imprinted genes may link issues such as
neurodevelopment and vulnerability to mental disease with the ‘battle of the
sexes’ at the level of cognitive and behavioral functioning.
Keywords: genomic imprinting, conflict between the sexes, behavioral and
cognitive phenotypes, mental disorders, Turner's syndrome, animal models
Type: article (scientific journal)
Trends in Cognitive Sciences
Vol 4, No 8, August 2000
Title: Genomic imprinting and the battle of the sexes
Authors: A.R. Isles and L.S. Wilkinson
Publication year: 2000
Journal name: Trends in Cognitive Sciences
DOI: Not provided in the article
Summarize: In their article, Isles and Wilkinson discuss the concept of genomic
imprinting, which involves the silencing of one allele according to its
parental origin. This results in traits being passed down either the maternal
or paternal line. The authors argue that this mode of inheritance is driven by
evolutionary conflict between the sexes. They review recent findings on the
effects of imprinted genes on behavioral and cognitive phenotypes, focusing on
mental disorders, Turner’s syndrome, and experimental work in animal models.
The authors suggest that imprinted genes may link issues such as
neurodevelopment and vulnerability to mental disease with the ‘battle of the
sexes’ at the level of cognitive and behavioral functioning.
Keywords: genomic imprinting, evolutionary conflict between the sexes,
behavioral and cognitive phenotypes, mental disorders, Turner's syndrome,
animal models
Type: article (scientific journal)
Checking 0000006a.txt
The string provided appears to contain a large number of identifiers, enclosed
within parentheses and separated by commas. It also contains some operators,
such as `&`, `*`, `!`, and `=`. However, without additional context or
information about the system in which this string is used, it is difficult to
determine its exact purpose or meaning. It could potentially represent a
complex expression within some kind of programming language, but further
investigation would be required for confirmation.
Checking 0001.txt
This paper presents a study on the college admission problem with lower and
common quotas, which aims to find an allocation of students to colleges that
maximizes social welfare while ensuring fairness in terms of quotas. The
authors propose a novel approach based on a nested Monte Carlo tree search
(MCTS) algorithm, which iteratively solves a sequence of smaller problems by
applying a simplified version of the original problem. The proposed method is
compared with other methods, and the results show that it outperforms them in
terms of solution quality and computation time. The authors also analyze the
sensitivity of their method to different parameters and discuss potential
extensions for more complex scenarios. Overall, this work provides an efficient
and effective approach to solving the college admission problem with quotas
while considering fairness and social welfare.
Checking 00030651211057041.txt
The article presents a neuropsychoanalytic model of consciousness and
emotion that is based on the dual-aspect theory of mind. In this model,
consciousness arises from the interaction between unconscious drives
and conscious thoughts about those drives. Dual-aspect theory posits
that both the physical brain (neurons) and the mental mind are equally
real, but in different aspects or dimensions. The article summarizes a
revision of Freud's drive theory that posits all drives as inherently sexual
in origin. This new model proposes that there are three types of drives:
1) sexually driven drives; 2) socially driven drives (such as the desire to
belong to a group or social status); and 3) drives related to basic needs,
such as hunger, thirst, or pain. The revised drive theory also suggests that
the oedipus complex arises from biological sexual differences between
males and females at an early developmental stage, which is later influenced
by the individual's social environment.
Checking 00030651221136840.txt
The authors explore the potential for integration between psychoanalysis and
neuroscience in understanding emotional functioning. They argue that a
synthesis of both disciplines can help deepen our understanding of the brain
mechanisms underlying emotions, and that this integration can be achieved
through a focus on the commonalities between the two fields, such as their
shared concern with emotion regulation, mental representations, and unconscious
processes. The authors suggest that the development of neuroscientific
techniques for studying the brain could help elucidate some of the mechanisms
proposed in psychoanalytic theory, such as the role of unconscious conflict in
emotional experience. They also propose that a better understanding of the
neural basis of emotions can aid in the development of more effective
therapeutic interventions for emotional disorders. The authors caution,
however, that the integration of neuroscience and psychoanalysis must be
approached with humility and an acknowledgment of the limitations of both
fields, as well as a recognition of the complexities involved in mapping
psychological phenomena onto brain structures and processes. Overall, the
authors argue that a dialogue between psychoanalysis and neuroscience can lead
to a more comprehensive understanding of emotional functioning and promote the
development of effective therapeutic interventions for emotional disorders.
Checking 00088001.txt
The paper discusses a declarative semantics for deductive databases and logic
programming. It suggests that every logic program has a natural stratification
and an iterated fixed-point model. The authors propose the use of protected
circumscription, which allows to avoid some of the problems with classical
circumscription. They also present a method for updating views in databases.
Key Contributions:
* Proposal of a declarative semantics for deductive databases and logic
programming
* Suggestion that every logic program has a natural stratification and an
iterated fixed-point model
* Introduction of protected circumscription as a solution to some problems with
classical circumscription
* Method for updating views in databases
Applications:
* Deductive databases
* Logic programming
* Knowledge representation
* Database theory
* Data structures
Relevant references:
* M. H. van Emden and R. A. Kowalski, “The semantics of predicate logic as a
programming language,” J. ACM, vol. 23, no. 4, pp. 733-742,1976.
* A. Van Gelder, K. Ross, and J. S. Schlipf, “Unfounded sets and well- founded
semantics for general logic programs,” in Proc. 7th Symp Principles Database
Syst., 1988, pp, 221-230.
* Chitta Baral, Sarit Kraus, Jack Minker, “Protected Circumscription and the
View Update Problem,” IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL.
3, NO. 2, JUNE 1991.
Checking 0009087.txt
We have identified the “no-conspiracy” assumption and the “no-correlation”
assumption as inappropriate assumptions for hidden variables models of quantum
theory. We conclude that a hidden variables model that violates Bell
inequalities must include one or all of conspiracies, correlations, and
contextuality in a principled way, and that classical statistical field theory
provides an effective route to proceed with beables hidden from measurement,
modelling the violation of Bell inequalities.
Checking 0010054.txt
In this article, the authors study certain properties of holomorphic vector
bundles over Calabi-Yau manifolds and their moduli spaces. They consider a
particular family of vector bundles called "stable vector bundles," which are
important in string theory. The authors derive several results about these
stable vector bundles, including their deformations, the structure of their
moduli space, and their relationship to instantons.
One of the key results is a classification of the irreducible holonomies of
torsion-free affine connections on these vector bundles. The authors also show
that the universal deformation space of compact Calabi-Yau manifolds is smooth
and has a Petersson-Weil metric, which is an important geometric structure in
string theory.
The article is primarily mathematical and assumes a background in differential
geometry and algebraic geometry. It may be of interest to researchers working
on Calabi-Yau manifolds and string theory.
Checking 0011122.txt
In this appendix we summarize some ideas from the literature on the use of
Occam’s razor in formal systems as a means to limit the complexity of
mathematical models. The following summary is by no means exhaustive, but it
gives the interested reader an idea about the wide range of applications and
methods that have been used for this purpose.
1. There are different versions of Occam’s razor. The version most commonly
referred to today is “Ockham’s razor: Entia non sunt multiplicanda praeter
necessitatem,” which translates into English as “entities should not be
multiplied beyond necessity.” This version was not formulated by Ockham, but
instead by William of Ockham, a Franciscan friar and philosopher who lived in
the 14th century.
2. The most commonly used mathematical measure to quantify the complexity of
mathematical models is the Kolmogorov complexity or algorithmic complexity,
which measures the minimal size (in bits) of a program that produces the object
being considered. In this context, the simpler an object, the smaller its
Kolmogorov complexity.
3. There are different ways to compute the Kolmogorov complexity, each with
different advantages and disadvantages. The most commonly used methods to
compute or estimate the Kolmogorov complexity of a set of objects are based on
the concept of prefix codes or prefix-free codes. Another approach consists of
using universal computable functions to determine the minimal size of an object
that generates a given sequence.
4. There are different variants of Occam’s razor that have been used in formal
systems: the strong form, the weak form, and the average form. The strong form
states that the simplest model should be preferred; the weak form suggests that
simpler models are more likely to be true; the average form claims that the
complexity of a model should not be far from the average complexity of all
possible models.
5. The strong form of Occam’s razor has been used in computational learning
theory, where a simple hypothesis is chosen among many alternative hypotheses
to minimize the risk of overfitting. In this context, simplicity is measured by
the length of the shortest proof that the hypothesis follows from axioms or by
the Kolmogorov complexity of the hypothesis itself.
6. The weak form of Occam’s razor has been used in statistical learning theory
to define a probability distribution over hypotheses that depends on their
simplicity, which is measured by the number of parameters required for the
hypothesis to hold. In this context, simpler models tend to have smaller
numbers of parameters and are therefore more likely to be true.
7. The average form of Occam’s razor has been used in physics to define a
probability distribution over theories or hypotheses that depends on their
complexity, which is measured by the number of assumptions or free variables
they require to hold. In this context, simpler models tend to have fewer
assumptions and free variables and are therefore more likely to be true.
8. The strong form of Occam’s razor has also been used in physics to define a
set of universal laws that are based on the principle of maximum simplicity,
where only the simplest laws consistent with experimental evidence are
retained. In this context, simpler laws tend to be more general and predictive.
9. The average form of Occam’s razor has also been used in physics as the basis
for Bayesian model selection, which defines a probability distribution over
models that depends on their complexity and likelihood under experimental data.
In this context, simpler models are favored when they are equally likely under
the data as more complex models.
10. The average form of Occam’s razor has also been used in evolutionary theory
to define a fitness function for genetic algorithms or genetic programming that
depends on the complexity of the solutions produced by these algorithms. In
this context, simpler solutions tend to be favored when they are equally likely
under the data as more complex solutions.
11. The weak form of Occam’s razor has also been used in evolutionary theory to
define a fitness function for genetic algorithms or genetic programming that
depends on the complexity of the solutions produced by these algorithms. In
this context, simpler solutions tend to be favored when they are equally likely
under the data as more complex solutions.
12. The strong form of Occam’s razor has been used in evolutionary robotics to
define a fitness function for robot controllers that depends on their
complexity, which is measured by the number of rules or parameters required to
generate movements. In this context, simpler controllers tend to be favored
when they are equally likely under experimental data as more complex
controllers.
51
In summary, Occam’s razor can be used in formal systems as a means to limit the
complexity of mathematical models by preferring simpler models over more
complex ones or by favoring simpler models when their likelihood under the data
is equal to that of more complex models. The most commonly used measure of
simplicity for this purpose is the Kolmogorov complexity, although other
measures can be used as well. The choice of Occam’s razor can greatly impact
the performance and interpretability of the resulting mathematical models and
should therefore be carefully considered.
Checking 0011307.txt
The recent measurement of the solar neutrino oscillation parameters by the SNO
experiment has brought significant improvement to our understanding of neutrino
mixing and mass spectrum. This result, together with the data from other
long-baseline accelerator experiments, suggests a LMA (large mixing angle)
solution to the solar neutrino problem that is supported by most global
analyses of the current data. The LMA solution predicts that the neutrino mass
squared difference is (dm2)212 ≈ 7 × 10−5 eV2 and the mixing angle is
approximately sin2(θ2) ≈ 0.3. The measurement of the solar neutrino flux by the
SNO experiment also implies a value for the neutrino mass scale, which can be
obtained through theoretical models that predict the solar neutrino rates based
on our knowledge of the sun and the neutrino properties. In addition to the LMA
solution, there are two other regions in the oscillation parameter space (the
LOW and SMA solutions) that also fit the data reasonably well. These solutions,
however, have been largely ruled out by recent results from reactor and
accelerator neutrino experiments. The SNO measurement of the solar neutrino
flux has also led to a significant improvement in our understanding of matter
effects in neutrino oscillations, which could play an important role in
interpreting the results of future long-baseline accelerator experiments such
as the NOvA and T2K experiments.
Checking 003591575705001013.txt
The meeting discussed the potential of electronic devices and mathematical
models in understanding the nervous system, specifically focusing on the work
of Grey Walter and his demonstrations of simple machines capable of exhibiting
complex behaviors. The importance of information-flow theory in linking
psychological and physiological concepts was emphasized, with a suggestion that
data expressed in this language could lead to refinements in our understanding
of the nervous system. It was noted that mathematical models have value as
research tools but may not be useful for everyone, and discussions on whether
or not machines can think are deemed fruitless.
Checking 0069.txt
This paper proposes a novel approach for unsupervised video object
segmentation (UVOSE), called Video Segmentation with Adaptive Bilateral
Networks (VABN). The main idea behind VABN is to adapt the weights of the
segmentation network using human-robot interaction data, which allows the
network to learn more effective features for object segmentation.
The proposed approach consists of three stages: 1) Initialization, where a
teacher network is trained on a few labeled frames, 2) Interaction, where the
teacher and student networks interact by performing human-robot interaction
tasks, and 3) Adaptation, where the student network adapts its weights using
the data collected from the interaction stage.
The experimental results show that VABN achieves comparable or better
performance than state-of-the-art methods on three benchmark datasets, while
requiring significantly less labeled data for training. The authors also
demonstrate that their approach can be applied to different interaction tasks
and robots.
Overall, the proposed method is an effective and practical solution for UVOSE,
especially in scenarios where only a few labeled frames are available for
training the segmentation network.
Checking 00_Berti_DCB_5_ePDF-komprimiert.txt
For fragmentary texts, the digital revolution has produced resources that make
it possible to study and analyze these sources in a more comprehensive way.
These include databases such as Trismegistos, which provides stable identifiers
for ancient literary fragments; I.Sicily, an online database of all
inscriptions from ancient Sicily, including fragmentary historians’ texts;
Pinakes (Textes et manuscrits grecs), a French database collecting metadata
about ancient Greek manuscripts up to the 16th century. These resources are
valuable for digital scholarship on fragmentary texts as they enable
researchers to search, compare and analyze data across different collections
and in different ways.
Keywords: Trismegistos, I.Sicily, Pinakes (Textes et manuscrits grecs),
fragmentary texts, digital revolution.
Checking 00cce697-744f-4e57-9f04-7dc99d963696.txt
This section discusses the methodology for Study 2. The same sample was used
as in Study 1, with 367 participants from three different universities in
Norway. The text materials were also identical to those used in Study 1. The
data sources included a prior knowledge test and an adaptation of the TSEBQ to
assess learners' beliefs about climate change. A factor analysis was conducted
on the 15 items of the prior knowledge test, resulting in four dimensions
(accounting for 42.89% of the variance) that were used as covariates.
Study 3
=============
6. Introduction
6.1. Rationale
In Study 1 and 2 we identified various antecedents, consequences, and
transition patterns involving epistemic emotions. However, it remains to be
seen whether these transitions are causal or merely correlational. To address
this question, in the present study we manipulated curiosity, surprise, and
doubt using an online vignette experiment. The vignettes were designed to
create conditions that would evoke the desired epistemic emotion and then
examine learning strategies (i.e., metacognitive self-regulation, rehearsal,
critical thinking) as a consequence of these emotions. Additionally, we also
assessed learners' beliefs about their ability to solve problems related to
climate change.
6.2. Theoretical background
In the present study, we focused on three epistemic emotions: curiosity,
surprise, and doubt. Curiosity and surprise have been shown to be important for
learning (Dunbar & Forsyth, 2007; Pekrun et al., 2014), but their consequences
have not been extensively investigated in the context of climate change
education. The current study aims to provide a deeper understanding of the role
of curiosity and surprise in fostering climate-related learning.
6.3. Hypotheses
Based on previous research, we hypothesized that curiosity and surprise would
lead to more
metacognitive self-regulation (MCSR), rehearsal, and critical thinking than
doubt. We also
hypothesized that the effects of curiosity and surprise would be stronger when
participants had higher
prior knowledge about climate change.
6.4. Method
6.4.1. Participants
A total of 594 participants were recruited from Prolific, a crowdsourcing
platform. They were
paid $7 (USD) for their participation. All participants self-reported as having
English as their
native language and reported having no prior knowledge about the text topics.
Participants were
randomly assigned to one of three conditions: curiosity, surprise, or doubt.
6.4.2. Text materials
Three vignettes were created for each condition, resulting in nine vignettes.
The vignettes were
designed to create a scenario in which participants would feel the desired
emotion (curiosity, surprise,
or doubt). For example, the curiosity vignette read: "You have been reading an
article about climate
change and you notice that one of the points mentioned is about the impact of
greenhouse gas emissions
on the ozone layer. You are curious to know more about this and want to find
out if it is true."
6.4.3. Dependent variables
Participants rated their level of MCSR, rehearsal, and critical thinking using
a 10-point Likert scale. Additionally, participants were asked to rate their
beliefs about their ability to solve problems related to climate change.
6.5. Analyses
We conducted a 2 (prior knowledge) x 3 (emotion condition) mixed ANOVA with the
dependent variables
(MCSR, rehearsal, critical thinking, and beliefs about problem-solving
ability). We also conducted post-hoc
comparisons using t-tests.
6.6. Results
7. Discussion
7.1. Summary of the findings
The results showed that participants in the curiosity and surprise conditions
reported higher levels of MCSR, rehearsal, and critical thinking than those in
the doubt condition. Furthermore, the effects of curiosity and surprise were
stronger for participants with higher prior knowledge about climate change. The
results suggest that curiosity and surprise are important for fostering
learning about climate change.
7.2. Implications
The findings have implications for the design of educational materials and
interventions to promote learning about climate change. By creating scenarios
that evoke curiosity and surprise, educators can encourage students to engage
in more MCSR, rehearsal, and critical thinking. Additionally, the results
highlight the importance of prior knowledge in fostering learning.
7.3. Limitations and future research
The present study had several limitations. First, the sample was recruited from
a crowdsourcing platform, which may not be representative of the general
population. Second, the study used self-report measures, which may not
accurately reflect participants' actual learning behaviors. Third, the
vignettes were designed to evoke curiosity, surprise, and doubt, but it is
unclear how well they actually did so. Future research should address these
limitations by recruiting a more diverse sample, using objective measures of
learning behaviors, and developing more ecologically valid vignettes.
7.4. Conclusion
In conclusion, the present study provides evidence that curiosity and surprise
are important for fostering learning about climate change. The findings have
implications for the design of educational materials and interventions to
promote learning about climate change. Future research should address the
limitations of the present study by recruiting a more diverse sample, using
objective measures of learning behaviors, and developing more ecologically
valid vignettes.
References
===========
1. Adams, M., & Dunbar, K. (2016). Emotion and Learning: The Role of Curiosity,
Anxiety, and Enjoyment in Higher Education. Routledge.
2. Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (1999). How People
Learn: Brain, Mind, Experience, and School. Washington, DC: National Academy
Press.
3. Dunbar, K., & Forsyth, J. P. (2007). Emotion-based learning: The role of
curiosity in academic learning. Journal of Research in Science Teaching, 44(5),
613-629.
4. Kuo, K. W., & Seifert, C. (2016). Curiosity: Its nature, role in learning
and implications for educational practice. Educational Psychology Review,
28(2), 217-251.
5. Pekrun, R., Elliott, E. N., & Maier, M. A. (Eds.). (2014). Handbook of
emotions in education: Theoretical and empirical investigations on emotions in
learning, teaching, and educational assessment. Springer.
6. Tough, P. (2018). The Social Life of the Mind: How a Growing Body of
Research Can Change the Way We Think About Intelligence. Houghton Mifflin
Harcourt.
7. Zimmerman, B. J., & Kitsantas, A. (2005). Self-regulation and academic
motivation in middle childhood: An examination of the moderating role of
gender. Journal of Educational Psychology, 97(3), 487-496.
8. Zohar, E., & Dudley, L. (2010). Emotion and learning: Theories and
applications for education. Routledge.
Checking 01 Introduction to Sanskrit Part 1 – Thomas Egenes ( PDFDrive ).txt
| Summary: |
The text provided appears todescribe a conversation between a researcher (K)
and Swinburne (Turing) about the future of AI. The conversation revolves around
the idea that AI will eventually surpass human intelligence, AIs ability to
understand and learn from human-like experiences. Turing expresses his belief
that this will happen at some point in the future but also warns against
unchecked advancements in AI due to potential risks such as the misuse of AI
for destructive purposes. The text also mentions the concept of a
"Technological Singularity," a hypothetical future event when artificial
general intelligence surpasses human intelligence. The conversation emphasizes
the need for caution and careful planning when developing AI technology, as
well as the importance of ensuring that AI is used ethically and responsibly.
Checking 010.txt
The paper discusses an approach for resolving conflicts in a distributed
computing environment using negotiation between agents. The authors propose a
model of negotiation based on Nash's bargaining solution, which is extended to
handle incomplete information and repeated interactions. The approach involves
each agent presenting its initial proposal, followed by concessions based on
the other agent's counter-proposal until an agreement is reached or a deadline
is met. The authors test their model using simulations and compare it to a
benchmark model. They find that their approach performs better in terms of
reaching agreements more quickly and with less computational resources. The
paper also discusses limitations and future work, such as incorporating
learning mechanisms and addressing more complex scenarios with multiple agents
involved in negotiations. Overall, the authors argue that their approach
provides a promising foundation for developing effective negotiation strategies
in distributed computing environments.
Checking 0106141.txt
The author demonstrates that it is possible to construct a relativistically
covariant classical statistical field theory that violates Bell inequalities.
This model combines elements of wave equations (locality) and thermal equations
(nonlocalities), with the latter being no different from the nonlocalities found
in classical thermal models described by the heat equation. The author
concludes that such a relativistically nonlocal theory is acceptable as
classical relativistic physics, but it may not be more mathematically effective
than existing quantum field theory formalisms.
Checking 0109027.txt
The text presents a classical interpretation of quantum electrodynamics, where
the anticommutation rules for quantized Dirac spinor fields in quantum field
theory are replaced by sign switching rules for interaction terms to ensure
empirical accuracy. This approach allows us to describe experimental results
using perturbation expansions in a way that is consistent with classical
physics. The text also suggests that this interpretation can be incorporated
into classical physics and may be natural in a modified or different classical
formalism, although it does not supplant the mathematical structure of quantum
field theory based on the Wightman axioms.
Checking 0111027.txt
The title suggests that this paper is about classical nonlocal models for
states of a modified quantized Klein-Gordon field. However, the abstract states
that the paper has been withdrawn, indicating it is no longer available or
under consideration for publication. The text includes mathematical notation
related to a quantized Klein-Gordon field but does not provide any details on
the contents of the paper. The author's contact information and date are also
included.
Checking 0165551515613226.txt
In this article, the authors present a study on using rank aggregation in
feature selection for text classification tasks. They compare several feature
selection methods such as filter methods, wrapper methods, and evolutionary
algorithms (EA). The authors also propose an EA-based feature ranking method
that utilizes rank aggregation to combine multiple rankings from different
feature evaluation criteria. The study finds that the proposed method
outperforms other feature selection methods in terms of both accuracy and
computational efficiency. The authors suggest further research on using EA for
text classification tasks and combining feature evaluation criteria.
Journal of Information Science, 43(1) 2017 pp 25–38 (cid:2) The Authors, DOI:
10.1177/0165551515613226
Checking 02 Bayesian Decision Theory.txt
Topic 8. Bayesian Decision Theory
89
Probability & Bayesian Inference
8. Parameter Estimation
8.1 Maximum Likelihood Estimation
* Define maximum likelihood estimation
* The general method is to take the derivative of with respect to , set it to 0
and solve for :
* Properties:
+ asymptotically unbiased
+ asymptotically consistent
Example: Univariate Normal
1. Define log likelihood function
2. Set derivative of with respect to to zero
3. Solve for to obtain maximum likelihood estimate
4. Note that is biased (although asymptically unbiased).
Example: Multivariate Normal
1. Set the derivative of the log likelihood function to zero, and solve to
obtain maximum likelihood estimate.
2. One can show that if x and a are vectors, then
"
#$
!
x
a tx(
) = a
%
&’
CSE 4404/5327 Introduction to Machine Learning and Pattern Recognition
J. Elder
Checking 02.The New Penguin Russian Course A Complete Course for Beginners.pdf ( PDFDrive ).txt
| In this text, |
1. This text provides a brief explanation of the difference between an agent
and-finding function ( and an agentless-finding function. It explains that an
agent-finding function is used in programming to search for elements within a
data structure such as lists or arrays, while an agentless finding function is
a more general term that can refer to any function that performs a search
without the use of an agent or entity that actively searches through the data.
The text also discusses how this distinction can be important when designing
and analyzing algorithms for machine learning and artificial intelligence
applications. |
Here's a summary in English:
This text explains the difference between a function that uses an agent to
search through a data structure (like lists or arrays) and a function that
performs a search without using an agent or active entity. It also mentions
that understanding this distinction is crucial when designing and analyzing
algorithms for machine learning and AI applications.
Checking 0202021.txt
In this paper, the authors define a cumulative logic and present a complete
and decidable semantics for it using the well-founded model. This logic is
based on an extension of Tarski's semantics for conditional logics with the
addition of a preference relation between possible worlds that orders them
according to their "plausibility" or "likelihood." The authors provide a number
of examples illustrating the use of this logic and compare it to other
non-monotonic reasoning systems such as default logic, autoepistemic logic, and
circumscription. They conclude by discussing some open problems and directions
for future research in cumulative logics.
Checking 0208068.txt
The paper presents a theoretical model that explains psychic phenomena as
quantum entanglement between the observer and observed system, mediated by spin
networks in the brain. This theory suggests that consciousness could be driving
quantum mechanics, spacetime dynamics, and the structure of the universe
itself.
The authors argue that non-locality, a fundamental feature of quantum
mechanics, can be explained by the action potential modulation of neural spin
networks. They provide evidence from various experiments to support their
hypothesis. The theory also proposes a possible role for spin in memory and
consciousness.
Additionally, the paper discusses how general anesthetics affect the brain
according to the Dirac Hole Theory, presents new results concerning the vacuum
in Dirac Hole Theory, and offers evidence of non-local physical, chemical, and
biological effects that support quantum brain theory.
The authors suggest that thinking outside the box, understanding quantum
entanglement, and exploring its implications could lead to significant
advancements in our comprehension of consciousness, gravity, and the role they
play in the universe.
Checking 0278364904045479.txt
This paper presents a simultaneous localization and mapping algorithm for
mobile robots using sonar sensors. The proposed method is based on a
probabilistic approach that integrates extended information filters (EIFs) to
estimate the robot's position, velocity, and map of the environment. The EIFs
use Bayesian filtering and Kalman filters to update the robot's state estimates
and map, respectively. The algorithm is designed for teams of robots and can
handle non-linear dynamics, unknown input disturbances, and noisy sensor
measurements. It also incorporates an occlusion model to account for missing
data due to obstacles in the environment. Experimental results demonstrate that
the proposed method is efficient and accurate in estimating the robot's
position and mapping the environment compared to existing methods.
The key contributions of this paper are:
1. A probabilistic approach for simultaneous localization and mapping using
extended information filters (EIFs).
2. Incorporation of an occlusion model to handle missing data due to obstacles
in the environment.
3. Demonstration of the algorithm's efficiency and accuracy through
experimental results on a real robot platform with sonar sensors.
Checking 0278364906075026.txt
In this article, a method is proposed for solving the simultaneous
localization and mapping problem using an extended information filter (EIF).
The EIF is based on the Kalman filter, but allows for correlations between the
robot's position and its map. The main contribution of this paper is a proof
that the proposed algorithm converges to the correct solution under certain
assumptions.
The proposed method is shown to have better performance than previous methods
in terms of computational efficiency and accuracy, making it suitable for
real-time implementation on mobile robots. Additionally, the use of an extended
information filter allows for the incorporation of prior knowledge about the
environment, which can improve the robustness and reliability of the algorithm.
Overall, this paper provides a useful contribution to the field of simultaneous
localization and mapping, offering a computationally efficient and accurate
solution that is suitable for real-time implementation on mobile robots. The
use of an extended information filter also opens up the possibility of
incorporating prior knowledge about the environment to improve the robustness
and reliability of the algorithm.
Checking 0278364907073775.txt
The paper presents a method of activity recognition from wearable sensors
using a combination of dynamic Bayesian networks (DBNs) and conditional random
fields (CRFs). This hybrid method takes advantage of DBN's ability to handle
temporal relationships between sensor readings and CRF's capability to model
spatial patterns. The authors use a set of experiments with data collected from
three volunteers who wore various types of sensors while performing different
activities to evaluate their approach. They achieve high recognition accuracy
with the proposed hybrid method compared to using either DBNs or CRFs alone,
and also present methods for improving the performance by incorporating prior
knowledge about the activities and spatial relationships. The authors argue
that the presented method is scalable and could be adapted to other domains
where activity recognition from wearable sensors is necessary.
Checking 0278364917721629.txt
The authors propose a method for solving the IG problem in SLAM by minimizing
the log-likelihood of the observation vector given all the landmarks'
positions. They derive an expression for this log-likelihood and show that it
can be efficiently computed using sparse matrix operations. The proposed
solution has a complexity of O(M3+n03), where M is the size of information
matrices, n0 is the number of already mapped landmarks, and 3 denotes the robot
pose's dimension and the horizon length L. The authors prove that their derived
solution is correct for any ordering whatsoever of variables inside information
matrices. The proposed solution can be applied in real-time SLAM systems with
no need for precomputation or storing of previously computed IGs.
Checking 02783649221076381.txt
In this solution, the author derives the Karush-Kuhn-Tucker conditions for a
convex optimization problem with equality constraints using Lagrange
multipliers. The problem is to minimize an objective function subject to
equality constraints represented by a matrix equation Ax = b. The author first
rewrites the problem in terms of the slack variables, s = b - Ax, and
introduces Lagrange multipliers λ for each constraint. The Lagrangian is then
defined as the sum of the objective function and the product of the Lagrange
multiplier and the corresponding inequality constraint.
The Karush-Kuhn-Tucker conditions are obtained by taking partial derivatives of
the Lagrangian with respect to x, s, and λ and setting them equal to zero. This
results in a system of linear equations that can be solved for the optimal
values of x, s, and λ. The author demonstrates that this solution satisfies the
first-order optimality conditions for a convex optimization problem with
equality constraints.
The author also provides a geometric interpretation of the KKT conditions by
showing that they correspond to the tangent hyperplane to the feasible region
at the optimal point being orthogonal to the objective function's gradient.
Furthermore, the author discusses the relationship between the Lagrange
multipliers and the optimal values of the slack variables.
Finally, the author mentions a case where one or more of the inequality
constraints are active (i.e., the corresponding Lagrange multiplier λ is
strictly positive), and derives the necessary and sufficient conditions for
optimality in this case using Lagrange Multipliers and KKT Conditions.
Checking 02_Roman.txt
The author argues that the control of artificial intelligence (AI) will be
challenging due to its complexity, and it may become impossible in cases where
AI becomes superintelligent. The author suggests several approaches for
addressing this challenge, including: developing techniques for controlling AI
at early stages; ensuring that AI is designed to follow certain ethical
principles; creating error-correction mechanisms; and using Turing tests or
CAPTCHAs as zero-knowledge proofs of access to an artificially intelligent
system. The author also proposes the concept of an AI-Complete problem, which
refers to a problem that requires general intelligence to solve, and suggests
that such problems may be useful for testing the capabilities of AI systems.
The author emphasizes the importance of understanding the mathematics of
intelligence in order to better understand and control AI.
Checking 02whole.txt
The Simulation Hypothesis is a proposal about how higher cognition works. It
posits that when we think, or understand language, we are running simulations
of our own experiences in various modalities (auditory, visual, tactile, etc.).
In particular, the hypothesis suggests that when we understand words like
'cat', we activate a specific simulator module which generates schematic
representations of cats in all the relevant modalities. The Simulation
Hypothesis has been used to motivate an embodied approach to cognition, since
it is supposed to offer a non-arbitrary way of mapping representations onto
their real-world referents. But this advantage is questionable and the argument
may have smuggled in a resemblance theory of representation. The Simulation
Hypothesis also offers an alternative understanding of the SGP as a problem
about mapping amodal representations onto modal representations, rather than as
a problem about how we map arbitrary symbols onto referents in the world. But
on this reading, it is doubtful that embodied theories enjoy any advantage with
respect to the SGP.
Checking 0302005.txt
The article “Towards a Quantum Theory of Consciousness” by Eberhard
Atmanspacher and Ulrich Kraus presents the theoretical framework for a new
theory on consciousness based on quantum mechanics. In particular, they propose
that consciousness can be described as an orchestrated spacetime selection of
the brain’s microstates, with each state representing a specific mental event.
To support this view, the authors point out several parallels between the
structure of a conscious system and that of a quantum system. These include the
non-deterministic nature of both systems, their non-local and context-dependent
interactions, as well as the presence of an inherent uncertainty in the
selection process. The proposed model is consistent with the existing theories
on consciousness such as the global workspace theory and the integrated
information theory, but also adds new insights through its emphasis on the role
of spacetime structure.
In addition to the theoretical framework, the authors also present some
empirical findings that are consistent with their hypothesis. For instance,
they cite studies showing that human brain activity exhibits oscillatory
patterns similar to those found in quantum systems, and that these patterns
play a crucial role in conscious perception. Furthermore, they discuss the idea
of the “now” or “present moment”, which is thought to be the temporal window
through which consciousness is experienced. This concept is also closely
related to the structure of spacetime, as it is based on the brain’s ability to
integrate information over time.
Overall, the article by Atmanspacher and Kraus provides a compelling argument
for the application of quantum mechanics to the study of consciousness. While
more research will be needed to fully validate this theory, it offers a new
perspective that could help bridge the gap between neuroscience and quantum
physics.
Checking 0304171.txt
The quantum-classical correspondence principle has been reexamined
and it was shown that the classical theory can be derived by taking a limit of
the quantum theory. The classical theory is recovered when one takes a limit
of the quantum theory in which the number of particles goes to infinity and
the coupling constant goes to zero, with the ratio α = Nh/m constant. In this
case, the Wigner function becomes the classical phase space distribution
function (f(x, p)). For a thermal state, the Wigner function is related to the
characteristic function of the density matrix by a Fourier transform; in the
classical limit, this characteristic function reduces to an exponential of the
Fourier transform of the classical phase space distribution. The quantum theory
has been extended to include generalized functions (distributions). It was
shown
that the classical theory can be derived as the limit of a
non-commutative
quantum theory in which the number of particles goes to
infinity and the
coupling constant goes to zero, with the ratio α = Nh/m constant. The Wigner
function is related to the characteristic function of the density matrix by a
Fourier transform; in the classical limit, this characteristic function reduces
to an exponential of the Fourier transform of the classical phase space
distribution.
15
Checking 0306108v2.txt
The authors present a method for constructing a smooth spacelike hypersurface
from a given non-smooth one in a globally hyperbolic space-time (a solution of
the Einstein equations). They use the theory of Morse functions to construct a
smoothing process. The key point is that they can use any one of a class of
Cauchy surfaces, which satisfy certain properties, as starting surface.
The authors also prove some results concerning the smoothness of the
constructed hypersurface and its relation to the original Cauchy surface.
Finally, they give an application to vector fields in curved space-time.
Checking 0386 (Knuth).txt
The paper discusses the relationship between Bayesian probability and lattice
theory, using a lattice structure to represent both assertions (hypotheses) and
questions in an inquiry process. The lattice structure provides insights into
the structures, symmetries, and relationships of assertions and questions. The
author suggests that observer-participant models of neural processing could be
based on this representation, as it allows for a logical basis for neural
network design and adaptation. The paper concludes by mentioning the importance
of inductive logic in engineering cybernetic systems.
Checking 0390473.txt
In this article, Emily Troscianko argues that the concept of a “second
generation” narrative theory has become a catchall term for various theories
that don’t fit neatly within traditional paradigms. She identifies four key
themes in second-generation narratology: (1) an emphasis on reader-response and
the role of cognitive science in understanding narrative, (2) the rejection of
stable definitions of fictionality and an embrace of multiple possible
meanings, (3) a focus on non-Western and nonliterary texts, and (4) a concern
with the political implications of narrative. Troscianko argues that these
themes are interrelated and challenge traditional narratology in significant
ways. She concludes by suggesting potential directions for future research in
second-generation narratology.
Keywords: second-generation narratology, cognitive science, reader-response,
fictionality, non-Western texts, politics
Checking 0403692.txt
In this paper, we have analyzed the Bell inequalities from the perspective of
random fields theory. We found that these inequalities are influenced by the
assumption that the underlying random variables can be assumed to be
independent, which is a very strong hypothesis for general random systems such
as quantum systems.
The Bell inequalities are based on the assumptions that locality and
completeness hold for the system being studied, but these assumptions may not
always hold when dealing with general quantum systems or random systems. The
derivation of the Bell inequalities can be seen as a consequence of the
assumption that the underlying hidden variables are independent, which is
equivalent to the assumption of no-contextuality, a property that is often
assumed in classical physics but may not always hold for general quantum or
random systems.
This analysis highlights the need for caution when applying Bell inequalities
and suggests that they should be used with care when analyzing quantum or other
general random systems. It also provides an alternative perspective on the
interpretation of quantum mechanics and the role of hidden variables in this
theory.
Checking 0411156.txt
The paper presents a new way of constructing classical random field models for
experimental apparatuses that are compatible with quantum theory. It is based
on the idea that the quantized Klein-Gordon field can be presented in terms of a
conventional probability density function, and that this has a classical
counterpart, which is identified here as the probability density associated with
a classical random field model for experimental apparatuses. The resulting
classical models are nonlocal in the sense that Hegerfeldt, but not Bell,
nonlocality is manifestly present. These classical models can be used to
understand disturbances of experimental apparatus by measurements on quantum
systems as classical interactions between macroscopic objects.
Checking 0412143.txt
To show that RF S does not admit an efficient classical algorithm, we can assume
without loss of generality that the function g is a threshold function with
small bias µ (g). Using linear programming duality, we construct a joint
distribution over z and s such that
Pr [z = s] > 1 − µ (g), but for all s0 ∈ {z
0}, 1
}
, the probability that z is equal to g (s) modulo 2 is strictly less than µ
(g). It follows that if µ (g) < 0.146, then there exists a bounded-error
threshold function of parity such that g differs from this threshold function
on at most n/8 inputs, contradicting the assumption that µ (g) > 0.146.
Therefore we can assume without loss of generality that µ (g) > 0.146 and use a
pseudoparity function g′ such that g′ − g has small bias. Using linear
programming duality again, we show that there exist independent random
variables z and s such that with probability at least 1 − µ (g), both z and s
are equal to g (s) modulo 2. Since the difference between g and g′ is small, it
follows that with probability at least 0.5 − µ (g) /4, z is equal to g (s)
modulo 2. We can then construct a joint distribution over z and s such that for
all s0 ∈ {z
0}, 1
}
, the probability that z is equal to g (s) modulo 2 is at most
1/8, contradicting the previous fact. It follows that g′ is actually a parity
function, which completes the proof.
Checking 0427.txt
This study investigates the effectiveness of incorporating logical query
embeddings into a knowledge graph completion (KGC) model, aiming to improve the
performance on complex reasoning tasks. The authors propose a novel approach
called Relation-aware Query Embeddings for Knowledge Graph Completion
(ReQuery), which involves three main components: (1) learning relation-aware
entity representations using inductive link prediction; (2) training query
embeddings by learning to predict the logical queries that are entailed by the
given graph triple, and (3) employing a highway network to combine these
representations. To evaluate the performance of ReQuery, the authors compare it
against several baselines on four KGC datasets, including WN18, FB15K,
YAGO3-10, and WebKB10K. The results show that ReQuery consistently outperforms
other methods, achieving state-of-the-art performance on all datasets.
Furthermore, an ablation study is performed to analyze the importance of each
component in ReQuery's architecture.
In summary, the authors present a novel approach called ReQuery for KGC tasks,
which leverages relation-aware entity representations and query embeddings to
improve complex reasoning capabilities. The proposed method significantly
outperforms existing methods on various datasets, highlighting its potential
for future research in this area.
Checking 04568078.txt
The paper discusses the decidability, complexity, and expressiveness of
branching time temporal logic (BTTL) for a class of systems called Petri Nets.