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We prove the Paquette-Zeitouni law of fractional logarithm (LFL) for the extreme eigenvalues [arXiv:1505.05627] in full generality, and thereby verify a conjecture from [arXiv:1505.05627]. Our result holds for any Wigner minor process and…

Probability · Mathematics 2025-10-02 Zhigang Bao , Giorgio Cipolloni , László Erdős , Joscha Henheik , Oleksii Kolupaiev

A new version of a strong law of large numbers for a ``good'' pairwise independent sequence of random variables (r.v.'s) with a small part of ``bad'' dependent r.v.'s is proposed. The main goal is to relax the assumption on the existence of…

Probability · Mathematics 2025-06-10 I. V. Kozlov , A. Yu. Veretennikov

We introduce a simple one-parameter game derived from a model describing the properties of a directed polymer in a random medium. At his turn, each of the two players picks a move among two alternatives in order to maximize his final score,…

Statistical Mechanics · Physics 2008-12-08 Clément Sire

The famous theorem of R.Aumann and M.Maschler states that the sequence of values of an N-stage zero-sum game G_N with incomplete information on one side converges as N tends to infinity, and the error term is bounded by a constant divided…

Computer Science and Game Theory · Computer Science 2013-12-30 Fedor Sandomirskiy

The strong law of large numbers for linear combinations of functions of order statistics ($L$-statistics) based on weakly dependent random variables is proven. We also establish the Glivenko--Cantelli theorem for $\phi$-mixing sequences of…

Probability · Mathematics 2007-06-13 Evgeny Baklanov

The purpose of this paper is to establish a general strong law of large numbers (SLLN) for arbitrary sequences of random variables (rv's) based on the squared indice method and to provide applications to SLLN of associated sequences. This…

Probability · Mathematics 2015-06-30 Harouna Sangare , Gane Samb Lo

In 2006, Varacca and V\"olzer proved that on finite graphs, omega-regular large sets coincide with omega-regular sets of probability 1, by using the existence of positional strategies in the related Banach-Mazur games. Motivated by this…

Logic in Computer Science · Computer Science 2013-07-18 Thomas Brihaye , Quentin Menet

An ideal strategy in zero-sum games should not only grant the player an average reward no less than the value of Nash equilibrium, but also exploit the (adaptive) opponents when they are suboptimal. While most existing works in Markov games…

Machine Learning · Computer Science 2022-06-15 Qinghua Liu , Yuanhao Wang , Chi Jin

Let the random variable $Z_{n,k}$ denote the number of increasing subsequences of length $k$ in a random permutation from $S_n$, the symmetric group of permutations of $\{1,...,n\}$. We show that $Var(Z_{n,k_n})=o((EZ_{n,k_n})^2)$ as $…

Probability · Mathematics 2007-05-23 Ross Pinsky

We prove a strong law of large numbers for a class of strongly mixing processes. Our result rests on recent advances in understanding of concentration of measure. It is simple to apply and gives finite-sample (as opposed to asymptotic)…

Probability · Mathematics 2008-07-30 Aryeh Kontorovich , Anthony Brockwell

An important -- but very demanding -- property in collective decision-making is strategyproofness, which requires that voters cannot benefit from submitting insincere preferences. Gibbard (1977) has shown that only rather unattractive rules…

Computer Science and Game Theory · Computer Science 2024-12-17 Felix Brandt , Patrick Lederer

Adversarial training, a special case of multi-objective optimization, is an increasingly prevalent machine learning technique: some of its most notable applications include GAN-based generative modeling and self-play techniques in…

Machine Learning · Statistics 2021-03-17 Gauthier Gidel , David Balduzzi , Wojciech Marian Czarnecki , Marta Garnelo , Yoram Bachrach

Casting machine learning as a type of search, we demonstrate that the proportion of problems that are favorable for a fixed algorithm is strictly bounded, such that no single algorithm can perform well over a large fraction of them. Our…

Machine Learning · Statistics 2017-04-20 George D. Montanez

We study online reinforcement learning in average-reward stochastic games (SGs). An SG models a two-player zero-sum game in a Markov environment, where state transitions and one-step payoffs are determined simultaneously by a learner and an…

Machine Learning · Computer Science 2017-12-05 Chen-Yu Wei , Yi-Te Hong , Chi-Jen Lu

The non-local game scenario provides a powerful framework to study the limitations of classical and quantum correlations, by studying the upper bounds of the winning probabilities those correlations offer in cooperation games where…

Quantum Physics · Physics 2020-07-07 Ricardo Faleiro

Real-world sequential decision making problems commonly involve partial observability, which requires the agent to maintain a memory of history in order to infer the latent states, plan and make good decisions. Coping with partial…

Machine Learning · Computer Science 2022-02-09 Yonathan Efroni , Chi Jin , Akshay Krishnamurthy , Sobhan Miryoosefi

Two-player (antagonistic) games on (possibly stochastic) graphs are a prevalent model in theoretical computer science, notably as a framework for reactive synthesis. Optimal strategies may require randomisation when dealing with inherently…

Computer Science and Game Theory · Computer Science 2024-11-25 James C. A. Main , Mickael Randour

In this paper, we consider stochastic monotone Nash games where each player's strategy set is characterized by possibly a large number of explicit convex constraint inequalities. Notably, the functional constraints of each player may depend…

Optimization and Control · Mathematics 2023-08-25 Zeinab Alizadeh , Afrooz Jalilzadeh , Farzad Yousefian

We consider how to make probability forecasts of binary labels. Our main mathematical result is that for any continuous gambling strategy used for detecting disagreement between the forecasts and the actual labels, there exists a…

Machine Learning · Computer Science 2007-05-23 Vladimir Vovk , Akimichi Takemura , Glenn Shafer

Optimizing strategic decisions (a.k.a. computing equilibrium) is key to the success of many non-cooperative multi-agent applications. However, in many real-world situations, we may face the exact opposite of this game-theoretic problem --…

Computer Science and Game Theory · Computer Science 2022-10-05 Jibang Wu , Weiran Shen , Fei Fang , Haifeng Xu