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In this paper, we prove super-polynomial lower bounds for the model of \emph{sum of ordered set-multilinear algebraic branching programs}, each with a possibly different ordering ($\sum \mathsf{smABP}$). Specifically, we give an explicit…

Computational Complexity · Computer Science 2024-02-20 Prerona Chatterjee , Deepanshu Kush , Shubhangi Saraf , Amir Shpilka

The classical branch-and-bound algorithm for the integer feasibility problem has exponential worst case complexity. We prove that it is surprisingly efficient on reformulated problems, in which the columns of the constraint matrix are…

Optimization and Control · Mathematics 2009-08-06 Gabor Pataki , Mustafa Tural

We propose a simple, powerful, and flexible machine learning framework for (i) reducing the search space of computationally difficult enumeration variants of subset problems and (ii) augmenting existing state-of-the-art solvers with…

Machine Learning · Computer Science 2019-02-25 Juho Lauri , Sourav Dutta

In this short paper, we give an upper bound for the number of different basic feasible solutions generated by the simplex method for linear programming problems having optimal solutions. The bound is polynomial of the number of constraints,…

Optimization and Control · Mathematics 2015-03-17 Tomonari Kitahara , Shinji Mizuno

Directed and undirected graphical models, also called Bayesian networks and Markov random fields, respectively, are important statistical tools in a wide variety of fields, ranging from computational biology to probabilistic artificial…

Combinatorics · Mathematics 2007-06-13 Sergi Elizalde , Kevin Woods

We provide a doubly exponential upper bound in $p$ on the size of forbidden pivot-minors for symmetric or skew-symmetric matrices over a fixed finite field $\mathbb{F}$ of linear rank-width at most $p$. As a corollary, we obtain a doubly…

Combinatorics · Mathematics 2014-12-24 Mamadou Moustapha Kanté , O-joung Kwon

Symbolic regression is a powerful system identification technique in industrial scenarios where no prior knowledge on model structure is available. Such scenarios often require specific model properties such as interpretability, robustness,…

A core challenge in program synthesis is taming the large space of possible programs. Since program synthesis is essentially a combinatorial search, the community has sought to leverage powerful combinatorial constraint solvers. Here,…

We contribute to the program of proving lower bounds on the size of branching programs solving the Tree Evaluation Problem introduced by Cook et. al. (2012). Proving a super-polynomial lower bound for the size of nondeterministic thrifty…

Computational Complexity · Computer Science 2013-11-19 Balagopal Komarath , Jayalal Sarma M. N

We study expression learning problems with syntactic restrictions and introduce the class of finite-aspect checkable languages to characterize symbolic languages that admit decidable learning. The semantics of such languages can be defined…

Logic in Computer Science · Computer Science 2023-03-22 Paul Krogmeier , P. Madhusudan

We consider the problem of succinctly encoding a static map to support approximate queries. We derive upper and lower bounds on the space requirements in terms of the error rate and the entropy of the distribution of values over keys: our…

Data Structures and Algorithms · Computer Science 2007-10-18 David Talbot , John Talbot

In this paper, we study the structure of set-multilinear arithmetic circuits and set-multilinear branching programs with the aim of showing lower bound results. We define some natural restrictions of these models for which we are able to…

Computational Complexity · Computer Science 2015-11-10 V. Arvind , S. Raja

We analyze Kumar's recent quadratic algebraic branching program size lower bound proof method (CCC 2017) for the power sum polynomial. We present a refinement of this method that gives better bounds in some cases. The lower bound relies on…

Computational Complexity · Computer Science 2022-12-27 Fulvio Gesmundo , Purnata Ghosal , Christian Ikenmeyer , Vladimir Lysikov

We present a general method for obtaining strong bounds for discrete optimization problems that is based on a concept of branching duality. It can be applied when no useful integer programming model is available, and we illustrate this with…

Data Structures and Algorithms · Computer Science 2019-08-22 J. G. Benade , J. N. Hooker

Minimizing empirical risk subject to a set of constraints can be a useful strategy for learning restricted classes of functions, such as monotonic functions, submodular functions, classifiers that guarantee a certain class label for some…

Machine Learning · Computer Science 2016-10-26 Andrew Cotter , Maya Gupta , Jan Pfeifer

The minimum common string partition problem is an NP-hard combinatorial optimization problem with applications in computational biology. In this work we propose the first integer linear programming model for solving this problem. Moreover,…

Artificial Intelligence · Computer Science 2014-05-23 Christian Blum , José A. Lozano , Pedro Pinacho Davidson

We analyze a simple randomized subgradient method for approximating solutions to stochastic systems of convex functional constraints, the only input to the algorithm being the size of minibatches. By introducing a new notion of what is…

Optimization and Control · Mathematics 2021-08-30 James Renegar , Song Zhou

We show that one can approximate the least fixed point solution for a multivariate system of monotone probabilistic polynomial equations in time polynomial in both the encoding size of the system of equations and in log(1/\epsilon), where…

Computational Complexity · Computer Science 2013-02-21 Kousha Etessami , Alistair Stewart , Mihalis Yannakakis

We consider the problem of partitioning the node set of a graph into $k$ sets of given sizes in order to \emph{minimize the cut} obtained using (removing) the $k$-th set. If the resulting cut has value $0$, then we have obtained a vertex…

Optimization and Control · Mathematics 2014-11-20 Ting Kei Pong , Hao Sun , Ningchuan Wang , Henry Wolkowicz

This paper is concerned with the analysis of the randomized subspace iteration for the computation of low-rank approximations. We present three different kinds of bounds. First, we derive both bounds for the canonical angles between the…

Numerical Analysis · Mathematics 2018-11-13 Arvind K. Saibaba