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Previous theoretical results pertaining to meta-learning on sequences build on contrived assumptions and are somewhat convoluted. We introduce new information-theoretic tools that lead to an elegant and very general decomposition of error…

Machine Learning · Computer Science 2024-01-30 Hong Jun Jeon , Jason D. Lee , Qi Lei , Benjamin Van Roy

A theorem prover without an extensive library is much less useful to its potential users. Algebra, the study of algebraic structures, is a core component of such libraries. Algebraic theories also are themselves structured, the study of…

Logic in Computer Science · Computer Science 2020-06-17 Jacques Carette , William M. Farmer , Yasmine Sharoda

The problem-solving in automated theorem proving (ATP) can be interpreted as a search problem where the prover constructs a proof tree step by step. In this paper, we propose a deep reinforcement learning algorithm for proof search in…

Machine Learning · Computer Science 2018-11-05 Mitsuru Kusumoto , Keisuke Yahata , Masahiro Sakai

Integrated Information Theory is one of the leading models of consciousness. It aims to describe both the quality and quantity of the conscious experience of a physical system, such as the brain, in a particular state. In this contribution,…

Neurons and Cognition · Quantitative Biology 2020-02-19 Johannes Kleiner , Sean Tull

This paper will develop a single framework for unifying, simplifying and extending our prior results about axiom systems that retain a partial knowledge of their own consistency, via an axiomatic declaration of self-consistency. Its perhaps…

Logic · Mathematics 2012-01-04 Dan E. Willard

A unified combinatorial definition of the information content and entropy of different types of patterns, compatible with the traditional concepts of information and entropy, going beyond the limitations of Shannon information interpretable…

Information Theory · Computer Science 2025-01-22 Zsolt Pocze

Recent advances in neural variational inference have spawned a renaissance in deep latent variable models. In this paper we introduce a generic variational inference framework for generative and conditional models of text. While traditional…

Computation and Language · Computer Science 2016-06-07 Yishu Miao , Lei Yu , Phil Blunsom

Determining whether a provided context contains sufficient information to answer a question is a critical challenge for building reliable question-answering systems. While simple prompting strategies have shown success on factual questions,…

Computation and Language · Computer Science 2026-03-24 Akriti Jain , Aparna Garimella

Verification of neural networks is currently a hot topic in automated theorem proving. Progress has been rapid and there are now a wide range of tools available that can verify properties of networks with hundreds of thousands of nodes. In…

Machine Learning · Computer Science 2022-02-11 Matthew L. Daggitt , Wen Kokke , Robert Atkey , Luca Arnaboldi , Ekaterina Komendantskya

An impossibility theorem demonstrates that a particular problem or set of problems cannot be solved as described in the claim. Such theorems put limits on what is possible to do concerning artificial intelligence, especially the…

Artificial Intelligence · Computer Science 2023-06-19 Mario Brcic , Roman V. Yampolskiy

In recent years, information-theoretic generalization bounds have gained increasing attention for analyzing the generalization capabilities of meta-learning algorithms. However, existing results are confined to two-step bounds, failing to…

Machine Learning · Statistics 2025-10-14 Wen Wen , Tieliang Gong , Yuxin Dong , Zeyu Gao , Yong-Jin Liu

In this paper, based on results of exact learning and test theory, we study arbitrary infinite binary information systems each of which consists of an infinite set of elements and an infinite set of two-valued functions (attributes) defined…

Computational Complexity · Computer Science 2022-01-13 Mikhail Moshkov

The ``impossibility theorem'' -- which is considered foundational in algorithmic fairness literature -- asserts that there must be trade-offs between common notions of fairness and performance when fitting statistical models, except in two…

Machine Learning · Computer Science 2023-02-14 Andrew Bell , Lucius Bynum , Nazarii Drushchak , Tetiana Herasymova , Lucas Rosenblatt , Julia Stoyanovich

Information Theory concepts and methodologies conform the background of how communication systems are studied and understood. They are mainly focused on the source-channel-receiver problem and on the asymptotic limits of accuracy and…

Adaptation and Self-Organizing Systems · Physics 2017-05-16 Nicolás Rubido , Celso Grebogi , Murilo S. Baptista

The present paper offers, in its first part, a unified approach for the derivation of families of inequalities for set functions which satisfy sub/supermodularity properties. It applies this approach for the derivation of information…

Information Theory · Computer Science 2022-04-29 Igal Sason

Inferring from inconsistency and making decisions are two problems which have always been treated separately by researchers in Artificial Intelligence. Consequently, different models have been proposed for each category. Different…

Artificial Intelligence · Computer Science 2012-07-09 Leila Amgoud

We try to establish a unified information theoretic approach to learning and to explore some of its applications. First, we define {\em predictive information} as the mutual information between the past and the future of a time series,…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Ilya Nemenman

This document has an unorthodox structure to accomplish an unorthodox goal: presenting the scaffolding for a zero-parameter Unified Theory of Life inside several dozen pages. Ideally, that length is short enough to be understood in a few…

Neurons and Cognition · Quantitative Biology 2018-01-03 William R. Softky

In our previous arXiv papers (more systematically the informational conception is presented in the paper "The Information as Absolute", 2010) it was rigorously shown that Matter in our Universe - and Universe as a whole - are some…

General Physics · Physics 2011-05-05 S. V. Shevchenko , V. V. Tokarevsky

We present a prototype of an integrated reasoning environment for educational purposes. The presented tool is a fragment of a proof assistant and automated theorem prover. We describe the existing and planned functionality of the theorem…

Human-Computer Interaction · Computer Science 2018-03-06 Mario Frank , Christoph Kreitz
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