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Empirically, many strategic settings are characterized by stable outcomes in which players' decisions are publicly observed, yet no player takes the opportunity to deviate. To analyze such situations in the presence of incomplete…

Econometrics · Economics 2024-04-12 Paul S. Koh

We consider two-player non zero-sum infinite duration games played on weighted graphs. We extend the notion of secure equilibrium introduced by Chatterjee et al., from the Boolean setting to this quantitative setting. As for the Boolean…

Computer Science and Game Theory · Computer Science 2016-10-03 Véronique Bruyère , Noémie Meunier , Jean-François Raskin

Context: Software engineering has a problem in that when we empirically evaluate competing prediction systems we obtain conflicting results. Objective: To reduce the inconsistency amongst validation study results and provide a more formal…

Software Engineering · Computer Science 2021-01-15 Martin Shepperd , Stephen G. MacDonell

Game-theoretic concepts have been extensively studied in economics to provide insight into competitive behaviour and strategic decision making. As computing systems increasingly involve concurrently acting autonomous agents, game-theoretic…

Formal Languages and Automata Theory · Computer Science 2022-07-01 Marta Kwiatkowska , Gethin Norman , David Parker , Gabriel Santos , Rui Yan

Predictive Business Process Monitoring is becoming an essential aid for organizations, providing online operational support of their processes. This paper tackles the fundamental problem of equipping predictive business process monitoring…

Machine Learning · Computer Science 2020-09-18 Riccardo Galanti , Bernat Coma-Puig , Massimiliano de Leoni , Josep Carmona , Nicolò Navarin

A major bottleneck in characterizing the failure modes of generative AI systems is the cost and time of annotation and evaluation. Consequently, adaptive testing paradigms have gained popularity, where one opportunistically decides which…

Artificial Intelligence · Computer Science 2026-05-11 Siyu Zhou , Patrick Vossler , Venkatesh Sivaraman , Yifan Mai , Jean Feng

We introduce a testing-by-betting framework that leverages predictions on unlabeled data to enhance the power of sequential hypothesis testing. Given limited samples from the joint distribution of $(X,Y)$, and additional unlabeled samples…

Machine Learning · Computer Science 2026-05-28 Yaniv Tenzer , Elad Tolochinsky , Yaniv Romano

Always-valid concentration inequalities are increasingly used as performance measures for online statistical learning, notably in the learning of generative models and supervised learning. Such inequality advances the online learning…

Machine Learning · Statistics 2022-11-21 Chi-Hua Wang , Wenjie Li

Traffic scenarios are inherently interactive. Multiple decision-makers predict the actions of others and choose strategies that maximize their rewards. We view these interactions from the perspective of game theory which introduces various…

Machine Learning · Computer Science 2020-04-28 Christian Muench , Frans A. Oliehoek , Dariu M. Gavrila

In the gambling foundation of probability theory, rationality requires that a subject should always (never) find desirable all nonnegative (negative) gambles, because no matter the result of the experiment the subject never (always)…

Optimization and Control · Mathematics 2018-11-21 Alessio Benavoli , Alessandro Facchini , Dario Piga , Marco Zaffalon

We use the martingale-theoretic approach of game-theoretic probability to incorporate imprecision into the study of randomness. In particular, we define a notion of computable randomness associated with interval, rather than precise,…

Probability · Mathematics 2017-05-05 Gert de Cooman , Jasper De Bock

We develop a dynamic version of the SSVI parameterisation for the total implied variance, ensuring that European vanilla option prices are martingales, hence preventing the occurrence of arbitrage, both static and dynamic. Insisting on the…

Pricing of Securities · Quantitative Finance 2021-02-03 Mehdi El Amrani , Antoine Jacquier , Claude Martini

In game theory, players have continuous expected payoff functions and can use fixed point theorems to locate equilibria. This optimization method requires that players adopt a particular type of probability measure space. Here, we introduce…

Optimization and Control · Mathematics 2007-05-23 Michael J. Gagen , Kae Nemoto

Explaining AI systems is fundamental both to the development of high performing models and to the trust placed in them by their users. The Shapley framework for explainability has strength in its general applicability combined with its…

Machine Learning · Statistics 2021-12-21 Christopher Frye , Colin Rowat , Ilya Feige

Simple stochastic games are turn-based 2.5-player games with a reachability objective. The basic question asks whether one player can ensure reaching a given target with at least a given probability. A natural extension is games with a…

Computer Science and Game Theory · Computer Science 2021-02-02 Pranav Ashok , Krishnendu Chatterjee , Jan Kretinsky , Maximilian Weininger , Tobias Winkler

The technique of ``testing by betting" frames nonparametric sequential hypothesis testing as a multiple-round game, where a player bets on future observations that arrive in a streaming fashion, accumulates wealth that quantifies evidence…

Machine Learning · Computer Science 2025-08-12 Can Chen , Jun-Kun Wang

Variational inequalities (VIs) encompass many fundamental problems in diverse areas ranging from engineering to economics and machine learning. However, their considerable expressivity comes at the cost of computational intractability. In…

Computer Science and Game Theory · Computer Science 2025-03-03 Brian Hu Zhang , Ioannis Anagnostides , Emanuel Tewolde , Ratip Emin Berker , Gabriele Farina , Vincent Conitzer , Tuomas Sandholm

This paper extends results of Mortimer and Williams (1991) about changes of probability measure up to a random time under the assumptions that all martingales are continuous and that the random time avoids stopping times. We consider…

Probability · Mathematics 2016-08-16 Dörte Kreher

A/B tests are typically analyzed via frequentist p-values and confidence intervals; but these inferences are wholly unreliable if users endogenously choose samples sizes by *continuously monitoring* their tests. We define *always valid*…

Statistics Theory · Mathematics 2019-07-18 Ramesh Johari , Leo Pekelis , David J. Walsh

We develop horizon-aware anytime-valid tests and confidence sequences for bounded means under a strict deadline $N$. Using the betting/e-process framework, we cast horizon-aware betting as a finite-horizon optimal control problem with state…

Methodology · Statistics 2026-03-23 Ege Onur Taga , Samet Oymak , Shubhanshu Shekhar
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