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This paper considers the use of a simple posterior sampling algorithm to balance between exploration and exploitation when learning to optimize actions such as in multi-armed bandit problems. The algorithm, also known as Thompson Sampling,…

Machine Learning · Computer Science 2014-02-04 Daniel Russo , Benjamin Van Roy

We design two incremental algorithms for computing an inclusion-minimal completion of an arbitrary graph into a cograph. The first one is able to do so while providing an additional property which is crucial in practice to obtain…

Data Structures and Algorithms · Computer Science 2020-01-23 Christophe Crespelle , Daniel Lokshtanov , Thi Ha Duong Phan , Eric Thierry

We study a general convex optimization problem, which covers various classic problems in different areas and particularly includes many optimal transport related problems arising in recent years. To solve this problem, we revisit the…

Optimization and Control · Mathematics 2022-05-18 Lei Yang , Kim-Chuan Toh

We settle the complexities of the maximum-cardinality bipartite matching problem (BMM) up to poly-logarithmic factors in five models of computation: the two-party communication, AND query, OR query, XOR query, and quantum edge query models.…

Data Structures and Algorithms · Computer Science 2022-08-05 Joakim Blikstad , Jan van den Brand , Yuval Efron , Sagnik Mukhopadhyay , Danupon Nanongkai

We give new approximation algorithms for the submodular joint replenishment problem and the inventory routing problem, using an iterative rounding approach. In both problems, we are given a set of $N$ items and a discrete time horizon of…

Data Structures and Algorithms · Computer Science 2019-12-03 Thomas Bosman , Neil Olver

We show how to efficiently solve problems involving a quantitative measure, here called energy, as well as a qualitative acceptance condition, expressed as a B\"uchi or Parity objective, in finite weighted automata and in one-clock weighted…

Logic in Computer Science · Computer Science 2024-07-22 Sven Dziadek , Uli Fahrenberg , Philipp Schlehuber-Caissier

The Laplace approximation is a popular method for constructing a Gaussian approximation to the Bayesian posterior and thereby approximating the posterior mean and variance. But approximation quality is a concern. One might consider using…

Statistics Theory · Mathematics 2025-06-17 Mikołaj J. Kasprzak , Ryan Giordano , Tamara Broderick

In this paper we define a new descriptional complexity measure for Deterministic Finite Automata, BC-complexity, as an alternative to the state complexity. We prove that for two DFAs with the same number of states BC-complexity can differ…

Formal Languages and Automata Theory · Computer Science 2014-05-23 Maris Valdats

A synchronizing word of a deterministic finite complete automaton is a word whose action maps every state to a single one. Finding a shortest or a short synchronizing word is a central computational problem in the theory of synchronizing…

Formal Languages and Automata Theory · Computer Science 2022-07-13 Marek Szykuła , Adam Zyzik

B* is a novel optimization framework that addresses a critical challenge in fixed-base manipulator robotics: optimal base placement. Current methods rely on pre-computed kinematics databases generated through sampling to search for…

Robotics · Computer Science 2025-09-15 Zihang Zhao , Leiyao Cui , Sirui Xie , Saiyao Zhang , Zhi Han , Lecheng Ruan , Yixin Zhu

The fully enriched μ-calculus is the extension of the propositional μ-calculus with inverse programs, graded modalities, and nominals. While satisfiability in several expressive fragments of the fully enriched μ-calculus is known…

Logic in Computer Science · Computer Science 2015-07-01 Piero A. Bonatti , Carsten Lutz , Aniello Murano , Moshe Y. Vardi

Addressing class imbalance is a central challenge in credit card fraud detection, as it directly impacts predictive reliability in real-world financial systems. To overcome this, the study proposes an enhanced workflow based on the…

Machine Learning · Computer Science 2026-02-09 Reza E. Fazel , Arash Bakhtiary , Siavash A. Bigdeli

Submodular optimization generalizes many classic problems in combinatorial optimization and has recently found a wide range of applications in machine learning (e.g., feature engineering and active learning). For many large-scale…

Data Structures and Algorithms · Computer Science 2023-04-11 Matthew Fahrbach , Vahab Mirrokni , Morteza Zadimoghaddam

Motivated by applications in machine learning, such as subset selection and data summarization, we consider the problem of maximizing a monotone submodular function subject to mixed packing and covering constraints. We present a tight…

Data Structures and Algorithms · Computer Science 2018-12-20 Eyal Mizrachi , Roy Schwartz , Joachim Spoerhase , Sumedha Uniyal

Submodular maximization is a general optimization problem with a wide range of applications in machine learning (e.g., active learning, clustering, and feature selection). In large-scale optimization, the parallel running time of an…

Data Structures and Algorithms · Computer Science 2023-04-11 Matthew Fahrbach , Vahab Mirrokni , Morteza Zadimoghaddam

While many applications of automata in formal methods can use nondeterministic automata, some applications, most notably synthesis, need deterministic or good-for-games (GFG) automata. The latter are nondeterministic automata that can…

Logic in Computer Science · Computer Science 2023-06-22 Bader Abu Radi , Orna Kupferman

This paper proposes a novel technique for the approximation of strong solutions $u \in C(\overline{\Omega}) \cap W^{2,n}_\mathrm{loc}(\Omega)$ to uniformly elliptic linear PDE of second order in nondivergence form with continuous leading…

Numerical Analysis · Mathematics 2026-04-10 Ngoc Tien Tran

In 1960, G. Gr\"atzer and E.\,T. Schmidt proved that every finite distributive lattice can be represented as the congruence lattice of a sectionally complemented finite lattice $L$. For $u \leq v$ in $L$, they constructed a sectional…

Rings and Algebras · Mathematics 2022-08-09 G. Grätzer , G. Klus , A. Nguyen

We study the optimal lower and upper complexity bounds for finding approximate solutions to the composite problem $\min_x\ f(x)+h(Ax-b)$, where $f$ is smooth and $h$ is convex. Given access to the proximal operator of $h$, for strongly…

Optimization and Control · Mathematics 2023-08-15 Zhenyuan Zhu , Fan Chen , Junyu Zhang , Zaiwen Wen

Finite-state tree automata are a well studied formalism for representing term languages. This paper studies the problem of determining the regularity of the set of instances of a finite set of terms with variables, where each variable is…

Symbolic Computation · Computer Science 2009-11-20 Omer Giménez , Guillem Godoy , Sebastian Maneth
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