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Related papers: Entropy-Based Strategies for Multi-Bracket Pools

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Probabilistic predictions are probability distributions over the set of possible outcomes. Such predictions quantify the uncertainty in the outcome, making them essential for effective decision making. By combining multiple predictions, the…

Machine Learning · Statistics 2024-11-26 Sam Allen , David Ginsbourger , Johanna Ziegel

We propose local prediction pools as a method for combining the predictive distributions of a set of experts conditional on a set of variables believed to be related to the predictive accuracy of the experts. This is done in a two step…

Methodology · Statistics 2023-08-28 Oscar Oelrich , Mattias Villani , Sebastian Ankargren

We study the existing algorithms that solve the multidimensional martingale optimal transport. Then we provide a new algorithm based on entropic regularization and Newton's method. Then we provide theoretical convergence rate results and we…

Probability · Mathematics 2018-12-31 Hadrien De March

Suppose that the outcomes of a roulette table are not entirely random, in the sense that there exists a successful betting strategy. Is there a successful `separable' strategy, in the sense that it does not use the winnings from betting on…

Logic · Mathematics 2019-04-18 George Barmpalias , Nan Fang , Andrew Lewis-Pye

This paper shows how to evolve numerically the maximum entropy probability distributions for a given set of constraints, which is a variational calculus problem. An evolutionary algorithm can obtain approximations to some well-known…

Methodology · Statistics 2020-02-07 Raul Rojas

We introduce the Tournament Rank Probability Score (TRPS) as a measure to evaluate and compare pre-tournament predictions, where predictions of the full tournament results are required to be available before the tournament begins. The TRPS…

Applications · Statistics 2019-12-17 Claus Thorn Ekstrøm , Hans Van Eetvelde , Christophe Ley , Ulf Brefeld

There seems to be an upper limit to predicting the outcome of matches in (semi-)professional sports. Recent work has proposed that this is due to chance and attempts have been made to simulate the distribution of win percentages to identify…

Applications · Statistics 2015-08-21 Albrecht Zimmermann

We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to…

Computer Science and Game Theory · Computer Science 2024-11-12 Xavier Allamigeon , Stéphane Gaubert , Ricardo D. Katz , Mateusz Skomra

Single-elimination tournaments are the standard paradigm both for the main tennis professional associations. Schedules are generated by allocating first seeded and then unseeded players with seeds prevented from encountering each other…

Physics and Society · Physics 2020-10-23 Federico Della Croce , Gabriele Dragotto , Rosario Scatamacchia

In collaborative forecast projects, the combining of multiple probabilistic forecasts into an ensemble is standard practice, with linear pooling being a common combination method. The weighting scheme of a linear pool should be tailored to…

Methodology · Statistics 2025-09-05 Spencer Wadsworth , Jarad Niemi

Entropy estimation plays a crucial role in various fields, such as information theory, statistical data science, and machine learning. However, traditional entropy estimation methods often struggle with complex data distributions.…

Methodology · Statistics 2025-05-16 Luca Scrucca

Recently, it has been shown how sampling actions from the predictive distribution over the optimal action-sometimes called Thompson sampling-can be applied to solve sequential adaptive control problems, when the optimal policy is known for…

Artificial Intelligence · Computer Science 2014-09-24 Pedro A. Ortega , Daniel A. Braun

The most important factors which contribute to the efficiency of game-theoretical algorithms are time and game complexity. In this study, we have offered an elegant method to deal with high complexity of game theoretic multi-objective…

Computer Science and Game Theory · Computer Science 2015-03-13 Mahsa Badami , Ali Hamzeh , Sattar Hashemi

This work proposes a unified framework for portfolio allocation, covering both asset selection and optimization, based on a multiple-hypothesis predict-then-optimize approach. The portfolio is modeled as a structured ensemble, where each…

Portfolio Management · Quantitative Finance 2025-11-19 Alejandro Rodriguez Dominguez , Muhammad Shahzad , Xia Hong

The Traveling Tournament Problem (TTP) is a challenging combinatorial optimization problem that has attracted the interest of researchers around the world. This paper proposes an improved search neighbourhood for the TTP that has been…

Data Structures and Algorithms · Computer Science 2010-07-06 Glenn Langford

Betting strategies are often expressed formally as martingales. A martingale is called integer-valued if each bet must be an integer value. Integer-valued strategies correspond to the fact that in most betting situations, there is a minimum…

Computer Science and Game Theory · Computer Science 2015-05-21 George Barmpalias , Rod G. Downey , Michael McInerney

We study the problem of whether a betting-strategy can be decomposed into an equivalent set of simpler betting-strategies, such as betting-strategies that bet on a restricted set of stages or bet on a restricted of favorable outcomes. We…

Probability · Mathematics 2022-03-08 George Barmpalias , Lu Liu

What is the relationship between plausibility logic and the principle of maximum entropy? When does the principle give unreasonable or wrong results? When is it appropriate to use the rule `expectation = average'? Can plausibility logic…

Probability · Mathematics 2016-05-19 P. G. L. Porta Mana

An accumulator is a bet that presents a rather unique payout structure, in that it combines multiple bets into a wager that can generate a total payout given by the multiplication of the individual odds of its parts. These potentially…

Artificial Intelligence · Computer Science 2020-04-21 Nassim Dehouche

This paper describes the N-Tuple Bandit Evolutionary Algorithm (NTBEA), an optimisation algorithm developed for noisy and expensive discrete (combinatorial) optimisation problems. The algorithm is applied to two game-based hyper-parameter…

Neural and Evolutionary Computing · Computer Science 2018-05-09 Simon M Lucas , Jialin Liu , Diego Perez-Liebana