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The distribution of reversible programs tends to a limit as their size increases. For problems with a Hamming distance fitness function the limiting distribution is binomial with an exponentially small chance (but non~zero) chance of…

Emerging Technologies · Computer Science 2018-08-22 W. B. Langdon

We establish risk bounds for Regularized Empirical Risk Minimizers (RERM) when the loss is Lipschitz and convex and the regularization function is a norm. In a first part, we obtain these results in the i.i.d. setup under subgaussian…

Statistics Theory · Mathematics 2021-01-07 Geoffrey Chinot , Guillaume Lecué , Matthieu Lerasle

Reverse search is a convenient method for enumerating structured objects, that can be used both to address theoretical issues and to solve data mining problems. This method has already been successfully developed to handle unordered trees.…

Discrete Mathematics · Computer Science 2022-05-13 Florian Ingels , Romain Azaïs

A regularity lemma for polynomials provides a decomposition in terms of a bounded number of approximately independent polynomials. Such regularity lemmas play an important role in numerous results, yet suffer from the familiar shortcoming…

Combinatorics · Mathematics 2026-05-26 Guy Moshkovitz , Dora Woodruff

Large reasoning models (LRMs) "think" by generating structured chain-of-thought (CoT) before producing a final answer, yet they still lack the ability to reason critically about safety alignment and are easily biased when a flawed premise…

A rank estimator in robust regression is a minimizer of a function which depends (in addition to other factors) on the ordering of residuals but not on their values. Here we focus on the optimization aspects of rank estimators. We…

Optimization and Control · Mathematics 2019-10-15 Michal Cerny , Miroslav Rada , Jaromir Antoch , Milan Hladik

A major challenge of reinforcement learning (RL) in real-world applications is the variation between environments, tasks or clients. Meta-RL (MRL) addresses this issue by learning a meta-policy that adapts to new tasks. Standard MRL methods…

Machine Learning · Computer Science 2023-10-03 Ido Greenberg , Shie Mannor , Gal Chechik , Eli Meirom

We study the reverse mathematics of the theory of countable second-countable topological spaces, with a focus on compactness. We show that the general theory of such spaces works as expected in the subsystem $\mathsf{ACA}_0$ of second-order…

Logic · Mathematics 2011-11-01 François G. Dorais

We investigate the strength of a randomness notion $\mathcal R$ as a set-existence principle in second-order arithmetic: for each $Z$ there is an $X$ that is $\mathcal R$-random relative to $Z$. We show that the equivalence between…

Logic · Mathematics 2019-09-04 André Nies , Paul Shafer

We present REARANK, a large language model (LLM)-based listwise reasoning reranking agent. REARANK explicitly reasons before reranking, significantly improving both performance and interpretability. Leveraging reinforcement learning and…

Information Retrieval · Computer Science 2025-05-27 Le Zhang , Bo Wang , Xipeng Qiu , Siva Reddy , Aishwarya Agrawal

Large language models are increasingly capable at closed-world mathematical reasoning, but research assistance also requires source-grounded use of the literature. When a proof reaches a non-trivial step, a useful assistant should determine…

Artificial Intelligence · Computer Science 2026-05-12 Zicheng Lyu , Wenjie Yang , Shengzhong Zhang , Zengfeng Huang

New status in quantum mechanics is connected with recent achievements in the inverse problem. With its help instead of about ten exactly solvable models which serve as a basis of the contemporary education there are infinite (!) number,…

Quantum Physics · Physics 2007-05-23 B. N. Zakhariev , V. M. Chabanov

Reversible computing is a concept reflecting physical reversibility. Until now several reversible systems have been investigated. In a series of papers Kenichi Morita defines the rotary element RE, that is a reversible logic element. By…

Other Computer Science · Computer Science 2015-03-17 Serban E. Vlad

The enterprise of comparing mathematical theorems according to their logical strength is an active area in mathematical logic. In this setting, called reverse mathematics, one investigates which theorems provably imply which others in a…

Recursive reasoning models such as Hierarchical Reasoning Model (HRM) and Tiny Recursive Model (TRM) show that small, weight-shared networks can solve compute-heavy and NP puzzles by iteratively refining latent states, but their training…

Artificial Intelligence · Computer Science 2026-03-18 Navid Hakimi

Recursive queries have been traditionally studied in the framework of datalog, a language that restricts recursion to monotone queries over sets, which is guaranteed to converge in polynomial time in the size of the input. But modern big…

Databases · Computer Science 2024-01-26 Mahmoud Abo Khamis , Hung Q. Ngo , Reinhard Pichler , Dan Suciu , Yisu Remy Wang

Large Language Models (LLMs) are increasingly deployed in agentic and retrieval-augmented generation (RAG) systems, where they must execute user-specified tasks over externally provided reference text. In practice, such context is often…

Artificial Intelligence · Computer Science 2026-05-29 Zeli Su , Zhankai Xu , Tianlei Chen , Longfei Zheng , Xiaolu Zhang , Jun Zhou , Wentao Zhang

Sorites is an ancient piece of paradoxical reasoning pertaining to sets with the following properties: (Supervenience) elements of the set are mapped into some set of "attributes", (Tolerance) if an element has a given attribute then so are…

Logic · Mathematics 2019-03-14 Damir D. Dzhafarov

We continue the project of the study of reverse mathematics principles inspired by cardinal invariants. In this article in particular we focus on principles encapsulating the existence of large families of objects that are in some sense…

Logic · Mathematics 2026-02-04 David Belanger , Chi Tat Chong , Rupert Hölzl , Frank Stephan

Existing approaches to learning to prove theorems focus on particular logics and datasets. In this work, we propose Monte-Carlo simulations guided by reinforcement learning that can work in an arbitrarily specified logic, without any human…

Artificial Intelligence · Computer Science 2022-04-07 Stanisław J. Purgał , Cezary Kaliszyk