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Classical primal-dual affine programming takes place over finite dimensional real vector spaces. This results in beautiful duality theory, connecting the optimal solu- tions of the primal maximization problem and the dual minimization…

Optimization and Control · Mathematics 2015-04-13 Tien Chih

The spectacular success of deep generative models calls for quantitative tools to measure their statistical performance. Divergence frontiers have recently been proposed as an evaluation framework for generative models, due to their ability…

Machine Learning · Statistics 2021-12-14 Lang Liu , Krishna Pillutla , Sean Welleck , Sewoong Oh , Yejin Choi , Zaid Harchaoui

It is well known that every finite simple group can be generated by two elements and this leads to a wide range of problems that have been the focus of intensive research in recent years. In this survey article we discuss some of the…

Group Theory · Mathematics 2017-10-31 Timothy C. Burness

A fine moduli space is constructed, for cyclic-by-$\mathsf{p}$ covers of an affine curve over an algebraically closed field $k$ of characteristic $\mathsf{p}>0$. An intersection of finitely many fine moduli spaces for cyclic-by-$\mathsf{p}$…

Algebraic Geometry · Mathematics 2019-08-13 Jianru Zhang

We find necessary and sufficient conditions for the finite separability of finitely generated commutative rings. Namely, we prove that every such ring is a finite extension of its torsion ideal $I_k$ where $k$ is square-free, and $I_k$ is a…

Rings and Algebras · Mathematics 2023-10-09 Stanislav Kublanovsky

The space of marked commutative rings on n given generators is a compact metrizable space. We compute the Cantor-Bendixson rank of any member of this space. For instance, the Cantor-Bendixson rank of the free commutative ring on n…

Commutative Algebra · Mathematics 2010-08-04 Yves Cornulier

Tensor networks, which are originally developed for characterizing complex quantum many-body systems, have recently emerged as a powerful framework for capturing high-dimensional probability distributions with strong physical…

Machine Learning · Computer Science 2026-03-13 Haotong Duan , Zhongming Chen , Ngai Wong

It is well-known that every regular language admits a unique minimal deterministic acceptor. Establishing an analogous result for non-deterministic acceptors is significantly more difficult, but nonetheless of great practical importance. To…

Formal Languages and Automata Theory · Computer Science 2023-06-16 Stefan Zetzsche , Alexandra Silva , Matteo Sammartino

We revisit the finite time analysis of policy gradient methods in the one of the simplest settings: finite state and action MDPs with a policy class consisting of all stochastic policies and with exact gradient evaluations. There has been…

Machine Learning · Computer Science 2021-12-14 Jalaj Bhandari , Daniel Russo

Matrix completion is a basic machine learning problem that has wide applications, especially in collaborative filtering and recommender systems. Simple non-convex optimization algorithms are popular and effective in practice. Despite recent…

Machine Learning · Computer Science 2018-07-24 Rong Ge , Jason D. Lee , Tengyu Ma

We discuss the log minimal model theory for log surfaces. We show that the log minimal model program, the finite generation of log canonical rings, and the log abundance theorem for log surfaces hold true under assumptions weaker than the…

Algebraic Geometry · Mathematics 2011-08-19 Osamu Fujino

Given an oriented surface of positive genus with finitely many punctures, we classify the finite orbits of the mapping class group action on the moduli space of semisimple complex special linear two dimensional representations of the…

Geometric Topology · Mathematics 2022-06-29 Indranil Biswas , Subhojoy Gupta , Mahan Mj , Junho Peter Whang

We explore the conjectured duality between a class of large $N$ matrix integrals, known as multicritical matrix integrals (MMI), and the series $(2m-1,2)$ of non-unitary minimal models on a fluctuating background. We match the critical…

High Energy Physics - Theory · Physics 2021-07-07 Dionysios Anninos , Beatrix Mühlmann

We consider infinite-horizon $\gamma$-discounted (linear) constrained Markov decision processes (CMDPs) where the objective is to find a policy that maximizes the expected cumulative reward subject to expected cumulative constraints. Given…

Machine Learning · Computer Science 2025-10-29 Xingtu Liu , Lin F. Yang , Sharan Vaswani

We consider the low rank matrix completion problem over finite fields. This problem has been extensively studied in the domain of real/complex numbers, however, to the best of authors' knowledge, there exists merely one efficient algorithm…

Information Theory · Computer Science 2023-08-23 Mahdi Soleymani , Qiang Liu , Hessam Mahdavifar , Laura Balzano

It is a classical problem to compute a minimal set of invariant polynomial generating the invariant ring of a finite group as an algebra. We present here an algorithm for the computation of minimal generating sets in the non-modular case.…

Commutative Algebra · Mathematics 2012-10-25 Simon King

In the first part of this paper we introduced an algorithm that uses reachable set approximation to approximate the minimum time function of linear control problems. To illustrate the error estimates and to demonstrate differences to other…

Optimization and Control · Mathematics 2016-01-01 Robert Baier , Thuy Thi Thien Le

Minimal model conjecture for a proper variety $X$ is that if $\kappa(X)\geq 0$, then $X$ has a minimal model with the abundance and if $\kappa =-\infty$, then $X$ is birationally equivalent to a variety $Y$ which has a fibration $Y \to Z$…

alg-geom · Mathematics 2008-02-03 Shihoko Ishii

We investigate the minimal number of generators $\mu$ and the depth of divisorial ideals over normal semigroup rings. Such ideals are defined by the inhomogeneous systems of linear inequalities associated with the support hyperplanes of the…

Commutative Algebra · Mathematics 2007-05-23 W. Bruns , J. Gubeladze

Generative models such as denoising diffusion models are quickly advancing their ability to approximate highly complex data distributions. They are also increasingly leveraged in scientific machine learning, where samples from the implied…

Machine Learning · Computer Science 2025-03-14 Jan-Hendrik Bastek , WaiChing Sun , Dennis M. Kochmann