Results for 'Statistical Learning Theory'

976 found
Order:
  1. A statistical learning approach to a problem of induction.Kino Zhao - manuscript
    At its strongest, Hume's problem of induction denies the existence of any well justified assumptionless inductive inference rule. At the weakest, it challenges our ability to articulate and apply good inductive inference rules. This paper examines an analysis that is closer to the latter camp. It reviews one answer to this problem drawn from the VC theorem in statistical learning theory and argues for its inadequacy. In particular, I show that it cannot be computed, in general, whether (...)
    Download  
     
    Export citation  
     
    Bookmark  
  2. Unified Inductive Logic: From Formal Learning to Statistical Inference to Supervised Learning.Hanti Lin - manuscript
    While the traditional conception of inductive logic is Carnapian, I develop a Peircean alternative and use it to unify formal learning theory, statistics, and a significant part of machine learning: supervised learning. Some crucial standards for evaluating non-deductive inferences have been assumed separately in those areas, but can actually be justified by a unifying principle.
    Download  
     
    Export citation  
     
    Bookmark  
  3. Information, learning and falsification.David Balduzzi - 2011
    There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as the length of the shortest program producing it [1]. The second, Shannon information, takes events as belonging to ensembles and quantifies the information resulting from observing the given event in terms of the number of alternate events that have been ruled out [2]. The third, statistical (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  4.  59
    The Foundations of the Mentalist Theory and the Statistical Machine Learning Challenge: Comments on Matthias Mahlmann’s Mind and Rights.Vincent Carchidi - forthcoming - Symposium on Matthias Mahlmann's Mind and Rights.
    Matthias Mahlmann’s Mind and Rights (M&R) argues that the mentalist theory of moral cognition—premised on an approach to the mind most closely associated with generative linguistics—is the appropriate lens through which to understand moral judgment’s roots in the mind. Specifically, he argues that individuals possess an inborn moral faculty responsible for the principled generation of moral intuitions. These moral intuitions, once sufficiently abstracted, generalized, and universalized by individuals, gave rise to the idea of human rights embodied in such conventions (...)
    Download  
     
    Export citation  
     
    Bookmark  
  5. Reliability in Machine Learning.Thomas Grote, Konstantin Genin & Emily Sullivan - 2024 - Philosophy Compass 19 (5):e12974.
    Issues of reliability are claiming center-stage in the epistemology of machine learning. This paper unifies different branches in the literature and points to promising research directions, whilst also providing an accessible introduction to key concepts in statistics and machine learning – as far as they are concerned with reliability.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  6. Falsification and future performance.David Balduzzi - manuscript
    We information-theoretically reformulate two measures of capacity from statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. We show these capacity measures count the number of hypotheses about a dataset that a learning algorithm falsifies when it finds the classifier in its repertoire minimizing empirical risk. It then follows from that the future performance of predictors on unseen data is controlled in part by how many hypotheses the learner falsifies. As a corollary we show that empirical (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  7. Semantic Information G Theory and Logical Bayesian Inference for Machine Learning.Chenguang Lu - 2019 - Information 10 (8):261.
    An important problem with machine learning is that when label number n>2, it is very difficult to construct and optimize a group of learning functions, and we wish that optimized learning functions are still useful when prior distribution P(x) (where x is an instance) is changed. To resolve this problem, the semantic information G theory, Logical Bayesian Inference (LBI), and a group of Channel Matching (CM) algorithms together form a systematic solution. MultilabelMultilabel A semantic channel in (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  8. (2 other versions)The explanation game: a formal framework for interpretable machine learning.David S. Watson & Luciano Floridi - 2020 - Synthese 198 (10):1–⁠32.
    We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players (...)
    Download  
     
    Export citation  
     
    Bookmark   18 citations  
  9. Machine learning in bail decisions and judges’ trustworthiness.Alexis Morin-Martel - 2023 - AI and Society:1-12.
    The use of AI algorithms in criminal trials has been the subject of very lively ethical and legal debates recently. While there are concerns over the lack of accuracy and the harmful biases that certain algorithms display, new algorithms seem more promising and might lead to more accurate legal decisions. Algorithms seem especially relevant for bail decisions, because such decisions involve statistical data to which human reasoners struggle to give adequate weight. While getting the right legal outcome is a (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  10.  87
    Mechanizing Induction.Ronald Ortner & Hannes Leitgeb - 2009 - In Dov Gabbay (ed.), The Handbook of the History of Logic. Elsevier. pp. 719--772.
    In this chapter we will deal with “mechanizing” induction, i.e. with ways in which theoretical computer science approaches inductive generalization. In the field of Machine Learning, algorithms for induction are developed. Depending on the form of the available data, the nature of these algorithms may be very different. Some of them combine geometric and statistical ideas, while others use classical reasoning based on logical formalism. However, we are not so much interested in the algorithms themselves, but more on (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  11. An Introduction to Artificial Psychology Application Fuzzy Set Theory and Deep Machine Learning in Psychological Research using R.Farahani Hojjatollah - 2023 - Springer Cham. Edited by Hojjatollah Farahani, Marija Blagojević, Parviz Azadfallah, Peter Watson, Forough Esrafilian & Sara Saljoughi.
    Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps mind (...)
    Download  
     
    Export citation  
     
    Bookmark  
  12. Fair machine learning under partial compliance.Jessica Dai, Sina Fazelpour & Zachary Lipton - 2021 - In Jessica Dai, Sina Fazelpour & Zachary Lipton (eds.), Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society. pp. 55–65.
    Typically, fair machine learning research focuses on a single decision maker and assumes that the underlying population is stationary. However, many of the critical domains motivating this work are characterized by competitive marketplaces with many decision makers. Realistically, we might expect only a subset of them to adopt any non-compulsory fairness-conscious policy, a situation that political philosophers call partial compliance. This possibility raises important questions: how does partial compliance and the consequent strategic behavior of decision subjects affect the allocation (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  13. The Acceptability of Online Learning Action Cell Session Practice to Tagumpay National High School Teachers.Ann Michelle S. Medina, Mari Cris O. Lim & Aldren E. Camposagrado - 2023 - Universal Journal of Educational Research 2 (2):99-109.
    This quantitative study explores the acceptability of Online Learning Action Cell (LAC) practice as a school-based professional development strategy for Tagumpay National High School (TNHS) teachers. The research was motivated by the Department of Education (DepEd) Order No. 35 s. 2016 which prompts public schools to comply with the implementation of LAC sessions because it has a positive impact on teachers’ beliefs and practices resulting in education reforms for learners’ benefit. However, in compliance with DepEd’s policy on maximizing Time-On-Task (...)
    Download  
     
    Export citation  
     
    Bookmark  
  14. Falsifiable implies Learnable.David Balduzzi - manuscript
    The paper demonstrates that falsifiability is fundamental to learning. We prove the following theorem for statistical learning and sequential prediction: If a theory is falsifiable then it is learnable -- i.e. admits a strategy that predicts optimally. An analogous result is shown for universal induction.
    Download  
     
    Export citation  
     
    Bookmark  
  15. New Development of Neutrosophic Probability, Neutrosophic Statistics, Neutrosophic Algebraic Structures, and Neutrosophic Plithogenic Optimizations.Florentin Smarandache & Yanhui Guo - 2022 - Basel, Switzerland: MDPI.
    This volume presents state-of-the-art papers on new topics related to neutrosophic theories, such as neutrosophic algebraic structures, neutrosophic triplet algebraic structures, neutrosophic extended triplet algebraic structures, neutrosophic algebraic hyperstructures, neutrosophic triplet algebraic hyperstructures, neutrosophic n-ary algebraic structures, neutrosophic n-ary algebraic hyperstructures, refined neutrosophic algebraic structures, refined neutrosophic algebraic hyperstructures, quadruple neutrosophic algebraic structures, refined quadruple neutrosophic algebraic structures, neutrosophic image processing, neutrosophic image classification, neutrosophic computer vision, neutrosophic machine learning, neutrosophic artificial intelligence, neutrosophic data analytics, neutrosophic deep learning, (...)
    Download  
     
    Export citation  
     
    Bookmark  
  16. Can Deep CNNs Avoid Infinite Regress/Circularity in Content Constitution?Jesse Lopes - 2023 - Minds and Machines 33 (3):507-524.
    The representations of deep convolutional neural networks (CNNs) are formed from generalizing similarities and abstracting from differences in the manner of the empiricist theory of abstraction (Buckner, Synthese 195:5339–5372, 2018). The empiricist theory of abstraction is well understood to entail infinite regress and circularity in content constitution (Husserl, Logical Investigations. Routledge, 2001). This paper argues these entailments hold a fortiori for deep CNNs. Two theses result: deep CNNs require supplementation by Quine’s “apparatus of identity and quantification” in order (...)
    Download  
     
    Export citation  
     
    Bookmark  
  17. Statistical learning of complex questions.Hartmut Fitz - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 2692--2698.
    Download  
     
    Export citation  
     
    Bookmark  
  18. Modes of Convergence to the Truth: Steps Toward a Better Epistemology of Induction.Hanti Lin - 2022 - Review of Symbolic Logic 15 (2):277-310.
    Evaluative studies of inductive inferences have been pursued extensively with mathematical rigor in many disciplines, such as statistics, econometrics, computer science, and formal epistemology. Attempts have been made in those disciplines to justify many different kinds of inductive inferences, to varying extents. But somehow those disciplines have said almost nothing to justify a most familiar kind of induction, an example of which is this: “We’ve seen this many ravens and they all are black, so all ravens are black.” This is (...)
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  19. Adaptive Channel Hopping for IEEE 802.15. 4 TSCH-Based Networks: A Dynamic Bernoulli Bandit Approach.Taheri Javan Nastooh - 2021 - IEEE Sensors Journal 21 (20):23667-23681.
    In IEEE 802.15.4 standard for low-power low-range wireless communications, only one channel is employed for transmission which can result in increased energy consumption, high network delay and poor packet delivery ratio (PDR). In the subsequent IEEE 802.15.4-2015 standard, a Time-slotted Channel Hopping (TSCH) mechanism has been developed which allows for a periodic yet fixed frequency hopping pattern over 16 different channels. Unfortunately, however, most of these channels are susceptible to high-power coexisting Wi-Fi signal interference and to possibly some other ISM-band (...)
    Download  
     
    Export citation  
     
    Bookmark  
  20. Pragmatism : A learning theory for the future.Bente Elkjaer - 2009 - In Knud Illeris (ed.), Contemporary Theories of Learning: Learning Theorists -- In Their Own Words. Routledge. pp. 74-89.
    A theory of learning for the future advocates the teaching of a preparedness to respond in a creative way to difference and otherness. This includes an ability to act imaginatively in situations of uncertainties. John Dewey’s pragmatism holds the key to such a learning theory his view of the continuous meetings of individuals and environments as experimental and playful. That pragmatism has not yet been acknowledged as a relevant learning theory for the future may (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  21. Algorithmic Fairness from a Non-ideal Perspective.Sina Fazelpour & Zachary C. Lipton - 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society.
    Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and (...)
    Download  
     
    Export citation  
     
    Bookmark   12 citations  
  22. Broomean(ish) Algorithmic Fairness?Clinton Castro - forthcoming - Journal of Applied Philosophy.
    Recently, there has been much discussion of ‘fair machine learning’: fairness in data-driven decision-making systems (which are often, though not always, made with assistance from machine learning systems). Notorious impossibility results show that we cannot have everything we want here. Such problems call for careful thinking about the foundations of fair machine learning. Sune Holm has identified one promising way forward, which involves applying John Broome's theory of fairness to the puzzles of fair machine learning. (...)
    Download  
     
    Export citation  
     
    Bookmark  
  23. (1 other version)Recipes for Science: An Introduction to Scientific Methods and Reasoning.Angela Potochnik, Matteo Colombo & Cory Wright - 2017 - New York: Routledge.
    There is widespread recognition at universities that a proper understanding of science is needed for all undergraduates. Good jobs are increasingly found in fields related to Science, Technology, Engineering, and Medicine, and science now enters almost all aspects of our daily lives. For these reasons, scientific literacy and an understanding of scientific methodology are a foundational part of any undergraduate education. Recipes for Science provides an accessible introduction to the main concepts and methods of scientific reasoning. With the help of (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  24. The mindsponge and BMF analytics for innovative thinking in social sciences and humanities.Quan-Hoang Vuong, Minh-Hoang Nguyen & Viet-Phuong La (eds.) - 2022 - Berlin, Germany: De Gruyter.
    Academia is a competitive environment. Early Career Researchers (ECRs) are limited in experience and resources and especially need achievements to secure and expand their careers. To help with these issues, this book offers a new approach for conducting research using the combination of mindsponge innovative thinking and Bayesian analytics. This is not just another analytics book. 1. A new perspective on psychological processes: Mindsponge is a novel approach for examining the human mind’s information processing mechanism. This conceptual framework is used (...)
    Download  
     
    Export citation  
     
    Bookmark   104 citations  
  25. Linguistic Competence and New Empiricism in Philosophy and Science.Vanja Subotić - 2023 - Dissertation, University of Belgrade
    The topic of this dissertation is the nature of linguistic competence, the capacity to understand and produce sentences of natural language. I defend the empiricist account of linguistic competence embedded in the connectionist cognitive science. This strand of cognitive science has been opposed to the traditional symbolic cognitive science, coupled with transformational-generative grammar, which was committed to nativism due to the view that human cognition, including language capacity, should be construed in terms of symbolic representations and hardwired rules. Similarly, linguistic (...)
    Download  
     
    Export citation  
     
    Bookmark  
  26. Embodying Autistic Cognition: Towards Reconceiving Certain 'Autism-Related' Behavioral Atypicalities as Functional.Michael D. Doan & Andrew Fenton - 2012 - In Jami L. Anderson & Simon Cushing (eds.), The Philosophy of Autism. Rowman & Littlefield Publishers.
    Some researchers and autistic activists have recently suggested that because some ‘autism-related’ behavioural atypicalities have a function or purpose they may be desirable rather than undesirable. Examples of such behavioural atypicalities include hand-flapping, repeatedly ordering objects (e.g., toys) in rows, and profoundly restricted routines. A common view, as represented in the Diagnostic and Statistical Manual of Mental Disorders (DSM) IV-TR (APA, 2000), is that many of these behaviours lack adaptive function or purpose, interfere with learning, and constitute the (...)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  27. GAMIFICATION IN GENETICS: EFFECTS OF GAMIFIED INSTRUCTIONAL MATERIALS ON THE STEM STUDENTS’ INTRINSIC MOTIVATION.Aaron Funa, Renz Alvin Gabay & Jhonner D. Ricafort - 2021 - Jurnal Pendidikan IPA Indonesia 10 (4):462-473.
    Gamification in education offers an innovative way of learning. However, some studies claim that, while it helps raise students’ motivation, the kind of motivation is extrinsic and, so, intrinsic motivation declines with time. The researchers used the descriptive research design to describe the STEM students’ intrinsic motivation along with the utilization of game elements in teaching genetics through a learning management system. The researchers collected quantitative data using the Intrinsic Motivation Inventory, which were analyzed through descriptive statistics and (...)
    Download  
     
    Export citation  
     
    Bookmark  
  28. (1 other version)Engineering social concepts: Feasibility and causal models.Eleonore Neufeld - 2024 - Philosophy and Phenomenological Research 109 (3):819-837.
    How feasible are conceptual engineering projects of social concepts that aim for the engineered concept to be deployed in people's ordinary conceptual practices? Predominant frameworks on the psychology of concepts that shape work on stereotyping, bias, and machine learning have grim implications for the prospects of conceptual engineers: conceptual engineering efforts are ineffective in promoting certain social‐conceptual changes. Since conceptual components that give rise to problematic social stereotypes are sensitive to statistical structures of the environment, purely conceptual change (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  29.  42
    Predictors of students' SQ3R in Learning Statistics During Distance Education: An Ordinal Logit Modeling.Leomarich Casinillo, Melbert Hungo & Rujube Hermano - 2024 - Jpi (Jurnal Pendidikan Indonesia) 13 (1):192-201.
    Studying statistics during distance education is challenging due to limitations and communication problems. This has an impact on learning activities that could be more optimal. This research aims to analyze students' SQ3R level in learning statistics and determine its significant predictors. This type of research is quantitative research. The research design of this study is complex correlational research. The data collection method uses a questionnaire. Data analysis techniques use descriptive and inferential statistics. Secondary data from existing research studies (...)
    Download  
     
    Export citation  
     
    Bookmark  
  30. The effect of teacher- and peer-assisted evaluative mediation on EFL learners’ metacognitive awareness development.Enayat A. Shabani - 2020 - Englisia: Journal of Language, Education, and Humanities 8 (1):58-78.
    Rooted in the heart of Vygotsky’s Sociocultural Theory, mediation has recently received considerable attention in the field of TEFL. The existing literature suggests that mediation can play an essential role in language learners’ performance development. In addition, learners need to know about their thinking process which is interpreted as metacognition. This study aimed to investigate the effect of teacher- and peer-assisted evaluative mediation on learners’ metacognitive awareness development. To this end, 40 homogenized intermediate EFL learners were selected using a (...)
    Download  
     
    Export citation  
     
    Bookmark  
  31. Instructional Leadership Practices of School Administrators: The Case of El Salvador City Division, Philippines.Ma Leah Lincuna & Manuel Caingcoy - 2020 - Commonwealth Journal of Academic Research 1 (2):12-32.
    School administrators are mandated to take the instructional leadership roles. On this premise, a study assessed the extent of instructional leadership practices of public elementary school administrators in El Salvador City Division, Philippines. Also, it explored their actual practices, challenges encountered, and the ways they overcome the challenges in practicing instructional leadership. It employed a mixed-method research design. It administered the adopted assessment tool on instructional leadership to 15 school administrators and 12 of them were involved in the individual interviews. (...)
    Download  
     
    Export citation  
     
    Bookmark  
  32. Navigating beyond “here & now” affordances—on sensorimotor maturation and “false belief” performance.Maria Brincker - 2014 - Frontiers in Psychology 5.
    How and when do we learn to understand other people’s perspectives and possibly divergent beliefs? This question has elicited much theoretical and empirical research. A puzzling finding has been that toddlers perform well on so-called implicit false belief (FB) tasks but do not show such capacities on traditional explicit FB tasks. I propose a navigational approach, which offers a hitherto ignored way of making sense of the seemingly contradictory results. The proposal involves a distinction between how we navigate FBs as (...)
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  33. Determination, uniformity, and relevance: normative criteria for generalization and reasoning by analogy.Todd R. Davies - 1988 - In T. Davies (ed.), Analogical Reasoning. Kluwer Academic Publishers. pp. 227-250.
    This paper defines the form of prior knowledge that is required for sound inferences by analogy and single-instance generalizations, in both logical and probabilistic reasoning. In the logical case, the first order determination rule defined in Davies (1985) is shown to solve both the justification and non-redundancy problems for analogical inference. The statistical analogue of determination that is put forward is termed 'uniformity'. Based on the semantics of determination and uniformity, a third notion of "relevance" is defined, both logically (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  34. The math is not the territory: navigating the free energy principle.Mel Andrews - 2021 - Biology and Philosophy 36 (3):1-19.
    Much has been written about the free energy principle (FEP), and much misunderstood. The principle has traditionally been put forth as a theory of brain function or biological self-organisation. Critiques of the framework have focused on its lack of empirical support and a failure to generate concrete, falsifiable predictions. I take both positive and negative evaluations of the FEP thus far to have been largely in error, and appeal to a robust literature on scientific modelling to rectify the situation. (...)
    Download  
     
    Export citation  
     
    Bookmark   31 citations  
  35. Learning to apply theory of mind.Rineke Verbrugge & Lisette Mol - 2008 - Journal of Logic, Language and Information 17 (4):489-511.
    In everyday life it is often important to have a mental model of the knowledge, beliefs, desires, and intentions of other people. Sometimes it is even useful to to have a correct model of their model of our own mental states: a second-order Theory of Mind. In order to investigate to what extent adults use and acquire complex skills and strategies in the domains of Theory of Mind and the related skill of natural language use, we conducted an (...)
    Download  
     
    Export citation  
     
    Bookmark   10 citations  
  36.  20
    Why All Mathematical Equations Have an Equal Sign in the Middle (Including Deviations and Applications Across All Fields of Mathematics).Angelito Malicse - manuscript
    Why All Mathematical Equations Have an Equal Sign in the Middle (Including Deviations and Applications Across All Fields of Mathematics) -/- Mathematics is a universal tool used to express relationships, patterns, and structures in both abstract and real-world settings. At the heart of this tool is the equal sign, which symbolizes balance and equivalence between two ideas. The equal sign ensures that what is expressed on one side of an equation corresponds directly to the other. However, in practical applications, perfect (...)
    Download  
     
    Export citation  
     
    Bookmark  
  37.  19
    Aligning AI with the Universal Formula for Balanced Decision-Making.Angelito Malicse - manuscript
    -/- Aligning AI with the Universal Formula for Balanced Decision-Making -/- Introduction -/- Artificial Intelligence (AI) represents a highly advanced form of automated information processing, capable of analyzing vast amounts of data, identifying patterns, and making predictive decisions. However, the effectiveness of AI depends entirely on the integrity of its inputs, processing mechanisms, and decision-making frameworks. If AI is programmed without a foundational understanding of natural laws, it risks reinforcing misinformation, bias, and societal imbalance. -/- Angelito Malicse’s universal formula, particularly (...)
    Download  
     
    Export citation  
     
    Bookmark  
  38. Theory of signs and statistical approach to big data in assessing the relevance of clinical biomarkers of inflammation and oxidative stress.Pietro Ghezzi, Kevin Davies, Aidan Delaney & Luciano Floridi - 2018 - Proceedings of the National Academy of Sciences of the United States of America 115 (10):2473-2477.
    Biomarkers are widely used not only as prognostic or diagnostic indicators, or as surrogate markers of disease in clinical trials, but also to formulate theories of pathogenesis. We identify two problems in the use of biomarkers in mechanistic studies. The first problem arises in the case of multifactorial diseases, where different combinations of multiple causes result in patient heterogeneity. The second problem arises when a pathogenic mediator is difficult to measure. This is the case of the oxidative stress (OS) (...) of disease, where the causal components are reactive oxygen species (ROS) that have very short half-lives. In this case, it is usual to measure the traces left by the reaction of ROS with biological molecules, rather than the ROS themselves. Borrowing from the philosophical theories of signs, we look at the different facets of biomarkers and discuss their different value and meaning in multifactorial diseases and system medicine to inform their use in patient stratification in personalized medicine. (shrink)
    Download  
     
    Export citation  
     
    Bookmark  
  39. Teacher Factors that Influence the Choice of Teaching Methods Used by Early Childhood Development Education Teachers in Keiyo South District.Betty Jebet Cheruiyot - 2019 - Africa International Journal of Multidisciplinary Research 1 (7).
    The untrained early childhood development education (ECDE) teacher tends to escape from children’s problems instead of dealing with them. They do not know how to deal with different age groups since they do not know what tasks to give which group of children. The type of training enables a teacher to escape the constraints of a curriculum. Once this issue can be established, preferably by research, it will ease the inconsistencies in the ECDE teacher training in Kenya. The purpose of (...)
    Download  
     
    Export citation  
     
    Bookmark  
  40. Principles and Philosophy of Linear Algebra: A Gentle Introduction.Paul Mayer - manuscript
    Linear Algebra is an extremely important field that extends everyday concepts about geometry and algebra into higher spaces. This text serves as a gentle motivating introduction to the principles (and philosophy) behind linear algebra. This is aimed at undergraduate students taking a linear algebra class - in particular engineering students who are expected to understand and use linear algebra to build and design things, however it may also prove helpful for philosophy majors and anyone else interested in the ideas behind (...)
    Download  
     
    Export citation  
     
    Bookmark  
  41. Intuitive Learning in Moral Awareness. Cognitive-Affective Processes in Mencius’ Innatist Theory.İlknur Sertdemir - 2022 - Academicus International Scientific Journal 13 (25):235-254.
    Mencius, referred to as second sage in Chinese philosophy history, grounds his theory about original goodness of human nature on psychological components by bringing in something new down ancient ages. Including the principles of virtuous action associated with Confucius to his doctrine, but by composing them along psychosocial development, he theorizes utterly out of the ordinary that makes all the difference to the school. In his argument stated a positive opinion, he explains the method of forming individuals' moral awareness (...)
    Download  
     
    Export citation  
     
    Bookmark  
  42. Adaptive Intelligent Tutoring System for learning Computer Theory.Mohammed A. Al-Nakhal & Samy S. Abu Naser - 2017 - European Academic Research 4 (10).
    In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent manner (...)
    Download  
     
    Export citation  
     
    Bookmark   13 citations  
  43. A Little More Logical: Reasoning Well About Science, Ethics, Religion, and the Rest of Life (2nd edition).Brendan Shea - 2024 - Rochester, MN: Thoughtful Noodle Books.
    In a world filled with information overload and complex problems, the ability to think logically is a superpower. "A Little More Logical" is your guide to mastering this essential skill. This engaging and accessible open educational resource is perfect for students, teachers, and lifelong learners who want to improve their critical thinking abilities and make better decisions in all aspects of life. -/- Through a series of fun and interactive chapters, "A Little More Logical" covers a wide range of topics, (...)
    Download  
     
    Export citation  
     
    Bookmark  
  44. Statistical resentment, or: what’s wrong with acting, blaming, and believing on the basis of statistics alone.David Enoch & Levi Spectre - 2021 - Synthese 199 (3-4):5687-5718.
    Statistical evidence—say, that 95% of your co-workers badmouth each other—can never render resenting your colleague appropriate, in the way that other evidence (say, the testimony of a reliable friend) can. The problem of statistical resentment is to explain why. We put the problem of statistical resentment in several wider contexts: The context of the problem of statistical evidence in legal theory; the epistemological context—with problems like the lottery paradox for knowledge, epistemic impurism and doxastic wrongdoing; (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  45. A Theory Explains Deep Learning.Kenneth Kijun Lee & Chase Kihwan Lee - manuscript
    This is our journal for developing Deduction Theory and studying Deep Learning and Artificial intelligence. Deduction Theory is a Theory of Deducing World’s Relativity by Information Coupling and Asymmetry. We focus on information processing, see intelligence as an information structure that relatively close object-oriented, probability-oriented, unsupervised learning, relativity information processing and massive automated information processing. We see deep learning and machine learning as an attempt to make all types of information processing relatively close (...)
    Download  
     
    Export citation  
     
    Bookmark  
  46. How to Learn from Theory-Dependent Evidence; or Commutativity and Holism: A Solution for Conditionalizers.J. Dmitri Gallow - 2014 - British Journal for the Philosophy of Science 65 (3):493-519.
    Weisberg ([2009]) provides an argument that neither conditionalization nor Jeffrey conditionalization is capable of accommodating the holist’s claim that beliefs acquired directly from experience can suffer undercutting defeat. I diagnose this failure as stemming from the fact that neither conditionalization nor Jeffrey conditionalization give any advice about how to rationally respond to theory-dependent evidence, and I propose a novel updating procedure that does tell us how to respond to evidence like this. This holistic updating rule yields conditionalization as a (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  47. On Regression Modeling for Students’ Attitude towards Statistics Online Learning in Higher Education.Leomarich Casinillo & Ginna Tavera - 2023 - St. Theresa Journal of Humanities and Social Sciences 9 (2):60-74.
    Students during the distance education were experiencing solitude and depression in their studies due to no social interaction which led to psychological suffering. In this article, college students' attitudes toward statistics learning were investigated, and its predictors by statistical modeling. Secondary data was extracted from a current study from the literature, summarized using descriptive statistics, and presented in tabular form. As for modeling the predictors of students' attitudes in learning statistics, it was done through multiple linear regression (...)
    Download  
     
    Export citation  
     
    Bookmark  
  48. A Bio-Logical Theory of Animal Learning.David Guez - 2009 - Biological Theory 4 (2):148-158.
    This article provides the foundation for a new predictive theory of animal learning that is based upon a simple logical model. The knowledge of experimental subjects at a given time is described using logical equations. These logical equations are then used to predict a subject’s response when presented with a known or a previously unknown situation. This new theory suc- cessfully anticipates phenomena that existing theories predict, as well as phenomena that they cannot. It provides a theoretical (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  49. Early Quantum Theory Genesis: Reconciliation of Maxwellian Electrodynamics, Thermodynamics and Statistical Mechanics.Rinat M. Nugayev - 2000 - Annales de la Fondation Louis de Broglie 25 (3-4):337-362.
    Genesis of the early quantum theory represented by Planck’s 1897-1906 papers is considered. It is shown that the first quantum theoretical schemes were constructed as crossbreed ones composed from ideal models and laws of Maxwellian electrodynamics, Newtonian mechanics, statistical mechanics and thermodynamics. Ludwig Boltzmann’s ideas and technique appeared to be crucial. Deriving black-body radiation law Max Planck had to take the experimental evidence into account. It forced him not to deduce from phenomena but to use more theory (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  50. Learning Organizations and Their Role in Achieving Organizational Excellence in the Palestinian Universities.Mazen J. Al Shobaki, Samy S. Abu Naser, Youssef M. Abu Amuna & Amal A. Al Hila - 2017 - International Journal of Digital Publication Technology 1 (2):40-85.
    The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the recovery (...)
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
1 — 50 / 976