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In a widely-studied class of multi-parametric optimization problems, the objective value of each solution is an affine function of real-valued parameters. Then, the goal is to provide an optimal solution set, i.e., a set containing an…

Optimization and Control · Mathematics 2021-12-14 Stephan Helfrich , Arne Herzel , Stefan Ruzika , Clemens Thielen

The study of phase transition phenomenon of NP complete problems plays an important role in understanding the nature of hard problems. In this paper, we follow this line of research by considering the problem of counting solutions of…

Artificial Intelligence · Computer Science 2011-02-25 Minghao Yin , Ping Huang

This article presents a general solution to the problem of computational complexity. First, it gives a historical introduction to the problem since the revival of the foundational problems of mathematics at the end of the 19th century.…

Computational Complexity · Computer Science 2023-12-25 Rami Zaidan

Model counting, or counting the satisfying assignments of a Boolean formula, is a fundamental problem with diverse applications. Given #P-hardness of the problem, developing algorithms for approximate counting is an important research area.…

Logic in Computer Science · Computer Science 2023-12-20 Kuldeep S. Meel , Supratik Chakraborty , S. Akshay

On the one hand, Constraint Satisfaction Problems allow one to declaratively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to declaratively…

Artificial Intelligence · Computer Science 2014-07-01 Frédéric Lardeux , Eric Monfroy , Broderick Crawford , Ricardo Soto

Single-level reformulations of (non-convex) distributionally robust optimization (DRO) problems are often intractable, as they contain semiinfinite dual constraints. Based on such a semiinfinite reformulation, we present a safe…

Optimization and Control · Mathematics 2025-06-09 J. Dienstbier , F. Liers , J. Rolfes

Deep reinforcement learning has achieved impressive successes yet often requires a very large amount of interaction data. This result is perhaps unsurprising, as using complicated function approximation often requires more data to fit, and…

Machine Learning · Computer Science 2020-11-20 Jonathan N. Lee , Aldo Pacchiano , Vidya Muthukumar , Weihao Kong , Emma Brunskill

We present efficient counting and sampling algorithms for random $k$-SAT when the clause density satisfies $\alpha \le \frac{2^k}{\mathrm{poly}(k)}.$ In particular, the exponential term $2^k$ matches the satisfiability threshold…

Data Structures and Algorithms · Computer Science 2024-11-06 Zongchen Chen , Aditya Lonkar , Chunyang Wang , Kuan Yang , Yitong Yin

We consider the hardness of computing additive approximations to output probabilities of random quantum circuits. We consider three random circuit families, namely, Haar random, $p=1$ QAOA, and random IQP circuits. Our results are as…

Quantum Physics · Physics 2022-06-14 Hari Krovi

In this paper, we study an adaptive finite element method for multiple eigenvalue problems of a class of second order elliptic equations. By using some eigenspace approximation technology and its crucial property which is also presented in…

Numerical Analysis · Mathematics 2013-09-18 Xiaoying Dai , Lianhua He , Aihui Zhou

We prove a complexity dichotomy theorem for a class of Holant problems on planar 3-regular bipartite graphs. The complexity dichotomy states that for every weighted constraint function $f$ defining the problem (the weights can even be…

Computational Complexity · Computer Science 2023-03-30 Jin-Yi Cai , Austen Z. Fan

We study the *refuter* problems for proof complexity lower bounds. Suppose $\varphi$ is a hard tautology that does not admit any length-$s$ proof in some proof system $P$. In the corresponding refuter problem, we are given (query access to)…

Computational Complexity · Computer Science 2026-03-25 Jiawei Li , Yuhao Li , Hanlin Ren

We connect the study of pseudodeterministic algorithms to two major open problems about the structural complexity of $\mathsf{BPTIME}$: proving hierarchy theorems and showing the existence of complete problems. Our main contributions can be…

Computational Complexity · Computer Science 2021-03-16 Zhenjian Lu , Igor C. Oliveira , Rahul Santhanam

We study the question of which counting problems admit f.p.r.a.s., under a structural complexity perspective. Since problems in #P with NP-complete decision version do not admit f.p.r.a.s. (unless NP = RP), we study subclasses of #P, having…

Computational Complexity · Computer Science 2018-01-09 Eleni Bakali

Many natural combinatorial problems can be expressed as constraint satisfaction problems. This class of problems is known to be NP-complete in general, but certain restrictions on the form of the constraints can ensure tractability. The…

Computational Complexity · Computer Science 2020-10-05 Dmitriy Zhuk

Let A be a matrix, c be any linear objective function and x be a fractional vector, say an LP solution to some discrete optimization problem. Then a recurring task in theoretical computer science (and in approximation algorithms in…

Data Structures and Algorithms · Computer Science 2011-04-26 Thomas Rothvoss

Random constraint satisfaction problems (CSPs) such as random $3$-SAT are conjectured to be computationally intractable. The average case hardness of random $3$-SAT and other CSPs has broad and far-reaching implications on problems in…

Computational Complexity · Computer Science 2019-11-11 Jonah Brown-Cohen , Prasad Raghavendra

Newton iteration (NI) is an almost 350 years old recursive formula that approximates a simple root of a polynomial quite rapidly. We generalize it to a matrix recurrence (allRootsNI) that approximates all the roots simultaneously. In this…

Computational Complexity · Computer Science 2017-10-10 Pranjal Dutta , Nitin Saxena , Amit Sinhababu

Counting the independent sets of a graph is a classical #P-complete problem, even in the bipartite case. We give an exponential-time approximation scheme for this problem which is faster than the best known algorithm for the exact problem.…

Data Structures and Algorithms · Computer Science 2021-09-10 Leslie Ann Goldberg , John Lapinskas , David Richerby

The field of fine-grained complexity aims at proving conditional lower bounds on the time complexity of computational problems. One of the most popular assumptions, Strong Exponential Time Hypothesis (SETH), implies that SAT cannot be…

Computational Complexity · Computer Science 2023-07-24 Tatiana Belova , Alexander S. Kulikov , Ivan Mihajlin , Olga Ratseeva , Grigory Reznikov , Denil Sharipov
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