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Related papers: Predicting Winning Lottery Numbers

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At the end, the house always wins! This simple truth holds for all public games of chance. Nevertheless, since lotteries have existed, people have tried everything to give luck a helping hand. This article compares objective scientific…

Other Statistics · Statistics 2026-03-27 Ralph Stömmer

Lotteries are a prevalent form of gambling between a seller and buyers. Designing a lottery requires a model of how buyers make decisions when confronted with uncertain outcomes. Cumulative prospect theory (CPT) is a descriptive model that…

Computer Science and Game Theory · Computer Science 2026-05-20 Shunta Akiyama , Mitsuaki Obara , Yasushi Kawase

In Major League Baseball, strategy and planning are major factors in determining the outcome of a game. Previous studies have aided this by building machine learning models for predicting the winning team of any given game. We extend this…

Machine Learning · Computer Science 2025-11-05 Morgan Allen , Paul Savala

Ensembling is a popular method used to improve performance as a last resort. However, ensembling multiple models finetuned from a single pretrained model has been not very effective; this could be due to the lack of diversity among ensemble…

Machine Learning · Computer Science 2022-05-25 Sosuke Kobayashi , Shun Kiyono , Jun Suzuki , Kentaro Inui

We propose two Bayesian multinomial-Dirichlet models to predict the final outcome of football (soccer) matches and compare them to three well-known models regarding their predictive power. All the models predicted the full-time results of…

Applications · Statistics 2020-06-16 Marcio A. Diniz , Rafael Izbicki , Danilo Lopes , Luis Ernesto Salasar

Quantum Decision Theory, advanced earlier by the authors, and illustrated for lotteries with gains, is generalized to the games containing lotteries with gains as well as losses. The mathematical structure of the approach is based on the…

Physics and Society · Physics 2018-02-20 V. I. Yukalov , D. Sornette

This paper introduces distribution-based prediction, a novel approach to using Large Language Models (LLMs) as predictive tools by interpreting output token probabilities as distributions representing the models' learned representation of…

Artificial Intelligence · Computer Science 2024-11-07 Caleb Bradshaw , Caelen Miller , Sean Warnick

Dirichlet-multinomial (DMN) distribution is commonly used to model over-dispersion in count data. Precise and fast numerical computation of the DMN log-likelihood function is important for performing statistical inference using this…

Machine Learning · Statistics 2020-07-24 Djallel Bouneffouf

Consider a gambling game in which we are allowed to repeatedly bet a portion of our bankroll at favorable odds. We investigate the question of how to minimize the expected number of rounds needed to increase our bankroll to a given target…

Probability · Mathematics 2011-12-06 Thomas P. Hayes

In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates. In this paper, we propose a new approach for estimating choice models in which we divide the systematic part of…

Machine Learning · Statistics 2020-09-23 Brian Sifringer , Virginie Lurkin , Alexandre Alahi

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

There have been several popular reports of various groups exploiting the deterministic nature of the game of roulette for profit. Moreover, through its history the inherent determinism in the game of roulette has attracted the attention of…

Chaotic Dynamics · Physics 2015-06-04 Michael Small , Chi Kong Tse

In two recent articles we have examined a generalization of the binomial distribution associated with a sequence of positive numbers, involving asymmetric expressions of probabilities that break the symmetry {\it win-loss}. We present in…

Mathematical Physics · Physics 2015-06-17 H. Bergeron , E. M. F. Curado , J. P. Gazeau , Ligia M. C. S. Rodrigues

Predicting the winner of an election is of importance to multiple stakeholders. To formulate the problem, we consider an independent sequence of categorical data with a finite number of possible outcomes in each. The data is assumed to be…

Applications · Statistics 2024-10-17 Soudeep Deb , Rishideep Roy , Shubhabrata Das

The recent lottery ticket hypothesis proposes that there is one sub-network that matches the accuracy of the original network when trained in isolation. We show that instead each network contains several winning tickets, even if the initial…

Machine Learning · Computer Science 2020-06-15 Kathrin Grosse , Michael Backes

We give a criterion under which the expected return on a ticket for certain large lotteries is positive. In this circumstance, we use elementary portfolio analysis to show that an optimal investment strategy includes a very small allocation…

History and Overview · Mathematics 2025-07-04 Aaron Abrams , Skip Garibaldi

The underlying loss landscapes of deep neural networks have a great impact on their training, but they have mainly been studied theoretically due to computational constraints. This work vastly reduces the time required to compute such loss…

Machine Learning · Computer Science 2021-12-17 Robert Bain

We develop and deploy a set of constraints for the purpose of calculating minimal sizes of lottery designs. Specifically, we find the minimum number of tickets of size six which are needed to match at least two balls on any draw of size…

Combinatorics · Mathematics 2024-06-18 David Cushing , David I. Stewart

Despite its unusual payout structure, the Canadian 6/49 Lotto is one of the few government sponsored lotteries that has the potential for a favorable strategy we call "buying the pot." By buying the pot we mean that a syndicate buys each…

Econometrics · Economics 2018-01-10 Steven D. Moffitt , William T. Ziemba

We report a new result on lotteries --- that a well-funded syndicate has a purely mechanical strategy to achieve expected returns of 10\% to 25\% in an equiprobable lottery with no take and no carryover pool. We prove that an optimal…

Econometrics · Economics 2018-01-10 Steven D. Moffitt , William T. Ziemba
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