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Self-normalized martingale inequalities lie at the heart of confidence ellipsoids for online least squares and, more broadly, many bandit and reinforcement-learning results. Yet existing vector and scalar results typically rely on bounded…

Machine Learning · Statistics 2026-05-05 Fan Chen , Jian Qian , Alexander Rakhlin , Nikita Zhivotovskiy

We prove a generalisation of Roth's theorem for arithmetic progressions to d-configurations, which are sets of the form {n_i+n_j+a}_{1 \leq i \leq j \leq d} where a, n_1,..., n_d are nonnegative integers, using Roth's original density…

Number Theory · Mathematics 2012-11-15 Jehanne Dousse

In this paper, we investigate the proof complexity of a wide range of substructural systems. For any proof system $\mathbf{P}$ at least as strong as Full Lambek calculus, $\mathbf{FL}$, and polynomially simulated by the extended Frege…

Logic · Mathematics 2020-08-21 Raheleh Jalali

Two recent approaches to computation in superposition reach different recursive capacity regimes: H\"anni et al. certify $\tilde{O}(d^{3/2})$ computable features in width $d$ via an approximate-linear recursive template, while Adler and…

Machine Learning · Computer Science 2026-05-05 Hector Borobia , Elies Seguí-Mas , Guillermina Tormo-Carbó

We present a forward sufficient dimension reduction method for categorical or ordinal responses by extending the outer product of gradients and minimum average variance estimator to multinomial generalized linear model. Previous work in…

Methodology · Statistics 2023-03-30 Harris Quach , Bing Li

In recent studies, linear recurrent neural networks (LRNNs) have achieved Transformer-level performance in natural language and long-range modeling, while offering rapid parallel training and constant inference cost. With the resurgence of…

Computation and Language · Computer Science 2024-04-10 Ting-Han Fan , Ta-Chung Chi , Alexander I. Rudnicky

Reverse Mathematics (RM for short) is a program in the foundations of mathematics with the aim of finding the minimal axioms required for proving theorems about countable and separable objects. RM usually takes place in second-order…

Logic · Mathematics 2015-07-28 Sam Sanders

Let $P:\{0,1\}^k \to \{0,1\}$ be a nontrivial $k$-ary predicate. Consider a random instance of the constraint satisfaction problem $\mathrm{CSP}(P)$ on $n$ variables with $\Delta n$ constraints, each being $P$ applied to $k$ randomly chosen…

Computational Complexity · Computer Science 2017-01-18 Pravesh K. Kothari , Ryuhei Mori , Ryan O'Donnell , David Witmer

We study the complexity of approximate representation and learning of submodular functions over the uniform distribution on the Boolean hypercube $\{0,1\}^n$. Our main result is the following structural theorem: any submodular function is…

Machine Learning · Computer Science 2013-04-03 Vitaly Feldman , Pravesh Kothari , Jan Vondrak

Nonlinear parametric inverse problems appear in many applications. Here, we focus on diffuse optical tomography (DOT) in medical imaging to recover unknown images of interest, such as cancerous tissue in a given medium, using a mathematical…

Numerical Analysis · Mathematics 2020-07-14 Selin Aslan , Eric de Sturler , Serkan Gugercin

We show exponential lower bounds on resolution proof length for pigeonhole principle (PHP) formulas and perfect matching formulas over highly unbalanced, sparse expander graphs, thus answering the challenge to establish strong lower bounds…

Computational Complexity · Computer Science 2025-04-02 Susanna F. de Rezende , Jakob Nordström , Kilian Risse , Dmitry Sokolov

Reverse Mathematics (RM hereafter) is a program in the foundations of mathematics where the aim is to identify the minimal axioms needed to prove a given theorem from ordinary, i.e. non-set theoretic, mathematics. This program has unveiled…

Logic · Mathematics 2022-09-30 Dag Normann , Sam Sanders

We contribute to a better understanding of the class of functions that can be represented by a neural network with ReLU activations and a given architecture. Using techniques from mixed-integer optimization, polyhedral theory, and tropical…

Machine Learning · Computer Science 2024-07-18 Christoph Hertrich , Amitabh Basu , Marco Di Summa , Martin Skutella

Reverse Mathematics is a program in the foundations of mathematics. Its results give rise to an elegant classification of theorems of ordinary mathematics based on computability. In particular, the majority of these theorems fall into only…

Logic · Mathematics 2015-07-28 Sam Sanders

Polynomial convergence bounds are considered for left, right, and split preconditioned GMRES. They include the cases of Weighted and Deflated GMRES for a linear system Ax = b. In particular, the case of positive definite A is considered.…

Numerical Analysis · Mathematics 2025-10-03 Nicole Spillane , Daniel B Szyld

The aim of Reverse Mathematics(RM for short)is to find the minimal axioms needed to prove a given theorem of ordinary mathematics. These minimal axioms are almost always equivalent to the theorem, working over the base theory of RM, a weak…

Logic · Mathematics 2023-09-01 Dag Normann , Sam Sanders

To comprehensively evaluate the mathematical reasoning capabilities of Large Language Models (LLMs), researchers have introduced abundant mathematical reasoning datasets. However, most existing datasets primarily focus on linear reasoning,…

Computation and Language · Computer Science 2026-02-25 Yuliang Ji , Fuchen Shen , Jian Wu , Qiujie Xie , Yue Zhang

Let $f: T\to \{ 0,1 \}$ be a Boolean function on the Boolean half-slice, $T$, \ie elements of $\{0,1\}^n$ with Hamming weight $n/2$. We show that if $f(x)+f(y)=f(x+y)$ holds with probability $\frac{1+\delta}{2}$ over a uniform pair $(x,y)$…

Computational Complexity · Computer Science 2026-05-27 Haakon Larsen , Tushant Mittal , Silas Richelson , Sourya Roy

We obtain a nontrivial upper bound for almost all elements of the sequences of real numbers which are multiplicative and at the prime indices are distributed according to the Sato--Tate density. Examples of such sequences come from…

Number Theory · Mathematics 2014-09-23 Florian Luca , Maksym Radziwill , Igor E. Shparlinski

We introduce linear programs encoding regular expressions of finite languages. We show that, given a language, the optimum value of the associated linear program is a lower bound on the size of any regular expression of the language.…

Formal Languages and Automata Theory · Computer Science 2017-12-08 Hamoon Mousavi