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The main goal of this article is to put some known results in a common perspective and to simplify their proofs. We start with a simple proof of a result of Vereshchagin saying that $\limsup_n C(x|n)$ equals $C^{0'}(x)$. Then we use the…

Logic · Mathematics 2012-04-03 Laurent Bienvenu , Andrej Muchnik , Alexander Shen , Nikolai Vereshchagin

Proof-Number Search is a best-first search algorithm with many successful applications, especially in game solving. As large-scale computing clusters become increasingly accessible, parallelization is a natural way to accelerate…

Artificial Intelligence · Computer Science 2026-02-10 Tomáš Čížek , Martin Balko , Martin Schmid

In this work, we consider "decision" variants of a monogamy-of-entanglement game by Tomamichel, Fehr, Kaniewski, and Wehner [New Journal of Physics '13]. In its original "search" variant, Alice prepares a (possibly entangled) state on…

Quantum Physics · Physics 2025-09-03 Andrea Coladangelo , Qipeng Liu , Ziyi Xie

This paper investigates the sublinear regret guarantees of two non-no-regret algorithms in zero-sum games: Fictitious Play, and Online Gradient Descent with constant stepsizes. In general adversarial online learning settings, both…

Machine Learning · Computer Science 2025-06-17 John Lazarsfeld , Georgios Piliouras , Ryann Sim , Andre Wibisono

In the Directed Disjoint Paths problem ($k$-DDP), we are given a digraph $k$ pairs of terminals, and the goal is to find $k$ pairwise vertex-disjoint paths connecting each pair of terminals. Bang-Jensen and Thomassen [SIAM J. Discrete Math.…

Data Structures and Algorithms · Computer Science 2025-04-29 Guilherme C. M. Gomes , Raul Lopes , Ignasi Sau

The aim of this paper is to present a result of discrete approximation of some class of stable self-similar stationary increments processes. The properties of such processes were intensively investigated, but little is known on the context…

Probability · Mathematics 2008-01-18 Clément Dombry , Nadine Guillotin-Plantard

We study two-player (zero-sum) concurrent mean-payoff games played on a finite-state graph. We focus on the important sub-class of ergodic games where all states are visited infinitely often with probability 1. The algorithmic study of…

Computer Science and Game Theory · Computer Science 2014-04-24 Krishnendu Chatterjee , Rasmus Ibsen-Jensen

Consider a scenario where a player chooses an action in each round $t$ out of $T$ rounds and observes the incurred cost after a delay of $d_{t}$ rounds. The cost functions and the delay sequence are chosen by an adversary. We show that in a…

Machine Learning · Computer Science 2022-05-16 Ilai Bistritz , Zhengyuan Zhou , Xi Chen , Nicholas Bambos , Jose Blanchet

In this paper, we resolve the computational complexity of a number of outstanding open problems with practical applications. Here is the list of problems we show to be PPAD-complete, along with the domains of practical significance:…

Computational Complexity · Computer Science 2009-04-10 Shiva Kintali , Laura J. Poplawski , Rajmohan Rajaraman , Ravi Sundaram , Shang-Hua Teng

We study the limiting behavior of the mixed strategies that result from optimal no-regret learning strategies in a repeated game setting where the stage game is any 2 by 2 competitive game. We consider optimal no-regret algorithms that are…

Computer Science and Game Theory · Computer Science 2022-03-03 Vidya Muthukumar , Soham Phade , Anant Sahai

We prove that any two-party correlation in the commuting operator model can be approximated using a tracially embeddable strategy, a class of strategies defined on a finite tracial von Neumann algebra, which we define in this paper. Using…

Quantum Physics · Physics 2025-09-17 Junqiao Lin

Many randomized algorithms can be derandomized efficiently using either the method of conditional expectations or probability spaces with low independence. A series of papers, beginning with work by Luby (1988), showed that in many cases…

Data Structures and Algorithms · Computer Science 2023-10-13 David G. Harris

A common challenge in nonparametric inference is its high computational complexity when data volume is large. In this paper, we develop computationally efficient nonparametric testing by employing a random projection strategy. In the…

Statistics Theory · Mathematics 2018-02-20 Meimei Liu , Zuofeng Shang , Guang Cheng

We present a new and surprisingly simple analysis of random-shift decompositions -- originally proposed by Miller, Peng, and Xu [SPAA'13]: We show that decompositions for exponentially growing scales $D = 2^0, 2^1, \ldots,…

Data Structures and Algorithms · Computer Science 2025-10-13 Rasmus Kyng , Maximilian Probst Gutenberg , Tim Rieder

By results of Dantzig (1951) and Adler (2013), computing the optimal solutions of a linear program is equivalent to finding optimal strategies in zero-sum bimatrix games. Dantzig's original result was incomplete, in the sense that the…

Optimization and Control · Mathematics 2026-04-27 Jesse Elliott , Constantin Ickstadt , Thorsten Theobald , Elias Tsigaridas

Randomized mechanisms can have good normative properties compared to their deterministic counterparts. However, randomized mechanisms are problematic in several ways such as in their verifiability. We propose here to derandomize such…

Computer Science and Game Theory · Computer Science 2024-05-16 Toby Walsh

This paper explores a fine-grained version of the Watrous conjecture, including the randomized and quantum algorithms with success probabilities arbitrarily close to $1/2$. Our contributions include the following: i) An analysis of the…

Computational Complexity · Computer Science 2023-10-24 Supartha Podder , Penghui Yao , Zekun Ye

A class of discrete Bidding Combinatorial Games that generalize alternating normal play was introduced by Kant, Larsson, Rai, and Upasany (2022). The major questions concerning optimal outcomes were resolved. By generalizing standard game…

Computer Science and Game Theory · Computer Science 2023-10-31 Prem Kant , Urban Larsson , Ravi K. Rai , Akshay V. Upasany

We introduce and investigate a new notion of the theory of approximation-the so-called degenerate approximation, i.e. approximation of the function of two (and more) variables (kernel) by means of degenerate function (kernel). We apply…

Probability · Mathematics 2013-03-14 E. Ostrovsky , L. Sirota

We show that natural classes of regularized learning algorithms with a form of recency bias achieve faster convergence rates to approximate efficiency and to coarse correlated equilibria in multiplayer normal form games. When each player in…

Computer Science and Game Theory · Computer Science 2015-12-14 Vasilis Syrgkanis , Alekh Agarwal , Haipeng Luo , Robert E. Schapire