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I describe a trick for training flow models using a prescribed rule as a surrogate for maximum likelihood. The utility of this trick is limited for non-conditional models, but an extension of the approach, applied to maximum likelihood of…

Machine Learning · Computer Science 2022-08-26 John S. Hyatt

We study distributed optimization in a cooperative multi-agent setting, where agents have to agree on the usage of shared resources and can communicate via a time-varying network to this purpose. Each agent has its own decision variables…

Optimization and Control · Mathematics 2017-04-20 Alessandro Falsone , Kostas Margellos , Simone Garatti , Maria Prandini

We study the low-energy dynamics of noncommutative $\N=2$ supersymmetric U(N) Yang-Mills theories in the Coulomb phase. Exact results are derived for the leading terms in the derivative expansion of the Wilsonian effective action. We find…

High Energy Physics - Theory · Physics 2010-02-03 Timothy J. Hollowood , Valentin V. Khoze , Gabriele Travaglini

We consider stochastic model predictive control of a multi-agent systems with constraints on the probabilities of inter-agent collisions. We first study a sample-based approximation of the collision probabilities and use this approximation…

Systems and Control · Computer Science 2011-08-17 Daniel Lyons , Jan-P. Calliess , Uwe D. Hanebeck

This work is motivated by numerical solutions to Hamilton-Jacobi-Bellman quasi-variational inequalities (HJBQVIs) associated with combined stochastic and impulse control problems. In particular, we consider (i) direct control, (ii)…

Numerical Analysis · Mathematics 2017-09-26 Parsiad Azimzadeh , Peter A. Forsyth

This paper considers a variation of the full-information secretary problem where the random variables to be observed are independent but not necessary identically distributed. The main result is a sharp lower bound for the optimal win…

Probability · Mathematics 2018-12-12 Pieter C. Allaart , Jose A. Islas

We obtain necessary and sufficient conditions for the admissible vectors of a new unitary non irreducible representation $U$. The group $G$ is an arbitrary semidirect product whose normal factor $A$ is abelian and whose homogeneous factor…

Representation Theory · Mathematics 2011-09-27 Filippo De Mari , Ernesto De Vito

We derive a new representation for $U$- and $V$-statistics. Using this representation, the asymptotic distribution of $U$- and $V$-statistics can be derived by a direct application of the Continuous Mapping theorem. That novel approach not…

Statistics Theory · Mathematics 2014-03-13 Eric Beutner , Henryk Zähle

In "Recognizing the Maximum of a Sequence", Gilbert and Mosteller analyze a full information game where n measurements from an uniform distribution are drawn and a player (knowing n) must decide at each draw whether or not to choose that…

Probability · Mathematics 2018-05-30 Marcos Costa Santos Carreira

Let (W_i, J_i) be a sequence of i.i.d. R_+ x R-valued random vectors. Considering the partial sum of the first component and the corresponding maximum of the second component, we are interested in the limit distributions that can be…

Probability · Mathematics 2016-09-09 Katharina Hees , Hans-Peter Scheffler

We consider the optimal risk sharing problem with a continuum of agents, modeled via a non-atomic measure space. Individual preferences are not assumed to be convex. We show the multiplicity of agents induces the value function to be…

Theoretical Economics · Economics 2025-09-12 Vasily Melnikov

In this paper, we study a distributed optimization problem for a class of high-order multi-agent systems with unknown dynamics. In comparison with existing results for integrators or linear agents, we need to overcome the difficulties…

Optimization and Control · Mathematics 2019-02-05 Yutao Tang

Given a sequence $(X_n)$ of symmetrical random variables taking values in a Hilbert space, an interesting open problem is to determine the conditions under which the series $\sum_{n=1}^\infty X_n$ is almost surely convergent. For…

Probability · Mathematics 2020-06-16 Safari Mukeru

We consider a toy model of interacting extrovert and introvert agents introduced earlier by Liu et al [Europhys. Lett. {\bf 100} (2012) 66007]. The number of extroverts, and introverts is $N$ each. At each time step, we select an agent at…

Physics and Society · Physics 2016-06-03 Deepak Dhar , Kevin E. Bassler , R. K. P. Zia

Given samples (x_1,...,x_m) and (z_1,...,z_n) which we believe are independent realizations of random variables X and Z respectively, where we further believe that Z=X+Y with Y independent of X, the problem is to estimate the distribution…

Computation · Statistics 2007-08-22 Colin Mallows

We perform Monte Carlo calculation of correlation functions in 4d N=4 super Yang-Mills theory on R*S^3 in the planar limit. In order to circumvent the well-known problem of lattice SUSY, we adopt the idea of a novel large-N reduction, which…

High Energy Physics - Lattice · Physics 2010-11-18 Masazumi Honda , Goro Ishiki , Sang-Woo Kim , Jun Nishimura , Asato Tsuchiya

This work is motivated by a question at the heart of unsupervised learning approaches: Assume we are collecting a number K of (subjective) opinions about some event E from K different agents. Can we infer E from them? Prima facie this seems…

Information Theory · Computer Science 2018-05-15 Janis Nötzel , Walter Swetly

In this paper, we settle the problem of learning optimal linear contracts from data in the offline setting, where agent types are drawn from an unknown distribution and the principal's goal is to design a contract that maximizes her…

Computer Science and Game Theory · Computer Science 2026-05-28 Mikael Møller Høgsgaard

We consider a control problem involving several agents coupled through multiple unit-demand resources. Such resources are indivisible, and each agent's consumption is modeled as a Bernoulli random variable. Controlling the number of such…

Systems and Control · Computer Science 2019-04-30 Syed Eqbal Alam , Robert Shorten , Fabian Wirth , Jia Yuan Yu

In this paper, we investigate the problem of deciding whether two standard normal random vectors $\mathsf{X}\in\mathbb{R}^{n}$ and $\mathsf{Y}\in\mathbb{R}^{n}$ are correlated or not. This is formulated as a hypothesis testing problem,…

Information Theory · Computer Science 2024-07-26 Dor Elimelech , Wasim Huleihel
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