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One powerful technique to solve NP-hard optimization problems in practice is branch-and-reduce search---which is branch-and-bound that intermixes branching with reductions to decrease the input size. While this technique is known to be very…

Data Structures and Algorithms · Computer Science 2018-10-26 Sebastian Lamm , Christian Schulz , Darren Strash , Robert Williger , Huashuo Zhang

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

We establish new hardness results for decision tree optimization problems, adding to a line of work that dates back to Hyafil and Rivest in 1976. We prove, under randomized ETH, superpolynomial lower bounds for two basic problems: given an…

Computational Complexity · Computer Science 2022-10-13 Caleb Koch , Carmen Strassle , Li-Yang Tan

Machine learning is increasingly used to guide branch-and-cut (B&C) for mixed-integer linear programming by learning score-based policies for selecting branching variables and cutting planes. Many approaches train on local signals from…

Optimization and Control · Mathematics 2026-02-02 Hongyu Cheng , Amitabh Basu

Extending the popular Answer Set Programming (ASP) paradigm by introspective reasoning capacities has received increasing interest within the last years. Particular attention is given to the formalism of epistemic logic programs (ELPs)…

Artificial Intelligence · Computer Science 2021-08-09 Viktor Besin , Markus Hecher , Stefan Woltran

This paper investigates linear programming based branch-and-bound using general disjunctions, also known as stabbing planes, for solving integer programs. We derive the first sub-exponential lower bound (in the encoding length $L$ of the…

Optimization and Control · Mathematics 2023-09-13 Max Gläser , Marc E. Pfetsch

We present a framework to address a class of sequential decision making problems. Our framework features learning the optimal control policy with robustness to noisy data, determining the unknown state and action parameters, and performing…

Machine Learning · Computer Science 2022-01-20 Amber Srivastava , Srinivasa M Salapaka

In this paper, we study arbitrary infinite binary information systems each of which consists of an infinite set called universe and an infinite set of two-valued functions (attributes) defined on the universe. We consider the notion of a…

Computational Complexity · Computer Science 2023-11-30 Kerven Durdymyradov , Mikhail Moshkov

We study fundamental block-structured integer programs called tree-fold and multi-stage IPs. Tree-fold IPs admit a constraint matrix with independent blocks linked together by few constraints in a recursive pattern; and transposing their…

Computational Complexity · Computer Science 2024-02-28 Christoph Hunkenschröder , Kim-Manuel Klein , Martin Koutecký , Alexandra Lassota , Asaf Levin

In this article, we study approximation properties of the variation spaces corresponding to shallow neural networks with a variety of activation functions. We introduce two main tools for estimating the metric entropy, approximation rates,…

Machine Learning · Statistics 2024-02-26 Jonathan W. Siegel , Jinchao Xu

We present a self-contained separation framework for P vs NP developed entirely within ZFC. The approach consists of: (i) a deterministic, radius-1 compilation from uniform polynomial-time Turing computation to local sum-of-squares (SoS)…

Computational Complexity · Computer Science 2026-01-09 Darren J. Edwards

In the decision tree computation model for Boolean functions, the depth corresponds to query complexity, and size corresponds to storage space. The depth measure is the most well-studied one, and is known to be polynomially related to…

Computational Complexity · Computer Science 2022-09-27 Yogesh Dahiya , Meena Mahajan

We show that one can approximate the least fixed point solution for a multivariate system of monotone probabilistic max(min) polynomial equations, referred to as maxPPSs (and minPPSs, respectively), in time polynomial in both the encoding…

Computational Complexity · Computer Science 2012-02-24 Kousha Etessami , Alistair Stewart , Mihalis Yannakakis

Based on a factorization of an input covariance matrix, we define a mild generalization of an upper bound of Nikolov (2015) and Li and Xie (2020) for the NP-Hard constrained maximum-entropy sampling problem (CMESP). We demonstrate that this…

Optimization and Control · Mathematics 2022-07-11 Zhongzhu Chen , Marcia Fampa , Jon Lee

It is known that there are classes of 2-CNFs requiring exponential size non-deterministic read-once branching programs to compute them. However, to the best of our knowledge, there are no superpolynomial lower bounds for branching programs…

Computational Complexity · Computer Science 2016-05-17 Igor Razgon

Bounded treewidth is one of the most cited combinatorial invariants, which was applied in the literature for solving several counting problems efficiently. A canonical counting problem is #SAT, which asks to count the satisfying assignments…

Artificial Intelligence · Computer Science 2023-06-22 Johannes K. Fichte , Markus Hecher , Patrick Thier , Stefan Woltran

Low-rank methods for semidefinite programming (SDP) have gained a lot of interest recently, especially in machine learning applications. Their analysis often involves determinant-based or Schatten-norm penalties, which are hard to implement…

Optimization and Control · Mathematics 2021-12-07 Mikhail Krechetov , Jakub Marecek , Yury Maximov , Martin Takac

We answer a problem posed in (G\'al, Kouck\'y, McKenzie 2008) regarding a restricted model of small-space computation, tailored for solving the GEN problem. They define two variants of "incremental branching programs", the syntactic variant…

Computational Complexity · Computer Science 2011-01-17 Dustin Wehr

In this paper, given a parameter $k$, we demonstrate an infinite class of {\sc cnf}s of treewidth at most $k$ of their primary graphs such that the equivalent nondeterministic read-once branching programs ({\sc nrobp}s) are of size at least…

Computational Complexity · Computer Science 2014-07-03 Igor Razgon

Branch and Bound (B&B) is the exact tree search method typically used to solve Mixed-Integer Linear Programming problems (MILPs). Learning branching policies for MILP has become an active research area, with most works proposing to imitate…

Machine Learning · Computer Science 2021-06-04 Giulia Zarpellon , Jason Jo , Andrea Lodi , Yoshua Bengio