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An approach for the description of stochastic systems is derived. Some of the variables in the system are studied forward in time, others backward in time. The approach is based on a perturbation expansion in the strength of the coupling…

Statistical Mechanics · Physics 2021-08-04 Piero Olla

This paper presents a model for a vehicle routing problem in which customer demands are stochastic and vehicles are divided into compartments. The problem is motivated by the needs of certain agricultural cooperatives that produce various…

Optimization and Control · Mathematics 2024-10-24 Juan Carlos Gonçalves-Dosantos , Laura Davila-Pena , Balbina Casas-Méndez

Stochastic matching is the stochastic version of the well-known matching problem, which consists in maximizing the rewards of a matching under a set of probability distributions associated with the nodes and edges. In most stochastic…

Optimization and Control · Mathematics 2024-05-01 Yuya Hikima , Yasunori Akagi , Hideaki Kim

We introduce two three sided adaptative systems as toy models to mimic the exchange of commodities between buyers and sellers. These models are simple extensions of the minority game, exhibiting similar behaviour as well as some new…

adap-org · Physics 2007-05-23 R. D'hulst , G. J. Rodgers

A matching in a two-sided market often incurs an externality: a matched resource may become unavailable to the other side of the market, at least for a while. This is especially an issue in online platforms involving human experts as the…

Artificial Intelligence · Computer Science 2018-10-30 Virag Shah , Lennart Gulikers , Laurent Massoulie , Milan Vojnovic

An agent-based modelling methodology for the joint price evolution of two stocks is put forward. The method models future multidimensional price trajectories reflecting how a class of agents rebalance their portfolios in an operational way…

Mathematical Finance · Quantitative Finance 2025-03-25 Dario Crisci , Sebastian E. Ferrando , Konrad Gajewski

Stacking, a potent ensemble learning method, leverages a meta-model to harness the strengths of multiple base models, thereby enhancing prediction accuracy. Traditional stacking techniques typically utilize established learning models, such…

Machine Learning · Computer Science 2024-10-31 Wei Wu , Liang Tang , Zhongjie Zhao , Chung-Piaw Teo

This paper formed part of a preliminary research report for a risk consultancy and academic research. Stochastic Programming models provide a powerful paradigm for decision making under uncertainty. In these models the uncertainties are…

Computational Finance · Quantitative Finance 2009-04-08 Sovan Mitra

In this paper, a simulation-based method for the analysis and design of abstracted models for a stochastic hybrid system is proposed. The accuracy of a model is evaluated in terms of its capability to reproduce the system output for all the…

Systems and Control · Computer Science 2014-05-29 M. Prandini , S. Garatti , R. Vignali

In this contribution, the properties of sub-stochastic matrix and super-stochastic matrix are applied to analyze the bipartite tracking issues of multi-agent systems (MASs) over signed networks, in which the edges with positive weight and…

Systems and Control · Electrical Eng. & Systems 2020-12-18 Lei Shi , Wei Xing Zheng , Jinliang Shao , Yuhua Cheng

Bilevel optimization problems are receiving increasing attention in machine learning as they provide a natural framework for hyperparameter optimization and meta-learning. A key step to tackle these problems is the efficient computation of…

Machine Learning · Statistics 2025-05-20 Riccardo Grazzi , Massimiliano Pontil , Saverio Salzo

We study variants of a stochastic game inspired by backgammon where players may propose to double the stake, with the game state dictated by a one-dimensional random walk. Our variants allow for different numbers of proposals and different…

Optimization and Control · Mathematics 2024-10-28 Haoru Ju , Daniel Leifer , Steven J. Miller , Sooraj A. Padmanabhan , Chenyang Sun , Luke Tichi , Benjamin Tocher , Kiley Wallace

We study a new two-time-scale stochastic gradient method for solving optimization problems, where the gradients are computed with the aid of an auxiliary variable under samples generated by time-varying MDPs controlled by the underlying…

Optimization and Control · Mathematics 2024-08-27 Sihan Zeng , Thinh T. Doan , Justin Romberg

Statistical and structural modeling represent two distinct approaches to data analysis. In this paper, we propose a set of novel methods for combining statistical and structural models for improved prediction and causal inference. Our first…

Econometrics · Economics 2020-06-11 Jiaming Mao , Jingzhi Xu

The quest for regular models of arithmetic surfaces allows different viewpoints and approaches: using valuations or a covering by charts. In this article, we sketch both approaches and then show in a concrete example, how surprisingly…

Algebraic Geometry · Mathematics 2017-01-06 Anne Frühbis-Krüger , Stefan Wewers

Two-sided marketplace platforms often run experiments to test the effect of an intervention before launching it platform-wide. A typical approach is to randomize individuals into the treatment group, which receives the intervention, and the…

Methodology · Statistics 2021-04-27 Hannah Li , Geng Zhao , Ramesh Johari , Gabriel Y. Weintraub

The global markets provide enterprises with selling opportunities and challenges in stabilizing operational strategies. From the perspective of production management, it is important to improve the profitability of an enterprise by…

Machine Learning · Computer Science 2022-07-28 Xiaoli Yan

To guarantee the well-functioning of electricity distribution networks, it is crucial to constantly ensure the demand-supply balance. To do this, one can control the means of production, but also influence the demand: demand-side management…

Optimization and Control · Mathematics 2021-03-01 Luce Brotcorne , Sébastien Lepaul , Léonard von Niederhäusern

In the option valuation literature, the shortcomings of one factor stochastic volatility models have traditionally been addressed by adding jumps to the stock price process. An alternate approach in the context of option pricing and…

Mathematical Finance · Quantitative Finance 2019-12-24 Gifty Malhotra , R. Srivastava , H. C. Taneja

In this paper, we investigate a mean-field singular stochastic optimal control problem for systems governed by mean-field regime-switching singular stochastic differential equations. The state process is assumed to depend on both a regular…

Optimization and Control · Mathematics 2025-12-01 Maalvladédon Ganet Somé , Edward Korveh
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