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We consider two classes of computations which admit taking linear combinations of execution runs: probabilistic sampling and generalized animation. We argue that the task of program learning should be more tractable for these architectures…

Logic in Computer Science · Computer Science 2015-12-17 Michael Bukatin , Steve Matthews

We study randomized variants of two classical algorithms: coordinate descent for systems of linear equations and iterated projections for systems of linear inequalities. Expanding on a recent randomized iterated projection algorithm of…

Optimization and Control · Mathematics 2008-06-19 D. Leventhal , A. S. Lewis

The purpose of this note is to give an exposition of some interesting combinatorics and convex geometry concepts that appear in algebraic geometry in relation to counting the number of solutions of a system of polynomial equations in…

Algebraic Geometry · Mathematics 2018-03-20 Kiumars Kaveh , A. G. Khovanskii

Probabilistic numerical methods (PNMs) solve numerical problems via probabilistic inference. They have been developed for linear algebra, optimization, integration and differential equation simulation. PNMs naturally incorporate prior…

We introduce a new technique for solving uni-parametric versions of linear programs, convex quadratic programs, and linear complementarity problems in which a single parameter is permitted to be present in any of the input data. We…

Optimization and Control · Mathematics 2022-03-25 Nathan Adelgren

We study system design problems stated as parameterized stochastic programs with a chance-constraint set. We adopt a Bayesian approach that requires the computation of a posterior predictive integral which is usually intractable. In…

Machine Learning · Statistics 2020-01-07 Prateek Jaiswal , Harsha Honnappa , Vinayak A. Rao

We present a numerical algorithm for finding real non-negative solutions to polynomial equations. Our methods are based on the expectation maximization and iterative proportional fitting algorithms, which are used in statistics to find…

Numerical Analysis · Mathematics 2010-04-02 Dustin Cartwright

Zero-sum Markov Stackelberg games can be used to model myriad problems, in domains ranging from economics to human robot interaction. In this paper, we develop policy gradient methods that solve these games in continuous state and action…

Computer Science and Game Theory · Computer Science 2024-01-24 Denizalp Goktas , Arjun Prakash , Amy Greenwald

To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables…

Artificial Intelligence · Computer Science 2009-03-09 Toby Walsh

With increasing game size, a problem of computational complexity arises. This is especially true in real world problems such as in social systems, where there is a significant population of players involved in the game, and the complexity…

Computer Science and Game Theory · Computer Science 2016-09-12 Tatsuya Iwase , Takahiro Shiga

This work aims to introduce the framework of polynomial optimization theory to solve fractional polynomial problems (FPPs). Unlike other widely used optimization frameworks, the proposed one applies to a larger class of FPPs, not…

Information Theory · Computer Science 2018-10-17 Andrea Pizzo , Alessio Zappone , Luca Sanguinetti

In this article, we consider a collection of geometric problems involving points colored by two colors (red and blue), referred to as bichromatic problems. The motivation behind studying these problems is two fold; (i) these problems appear…

Computational Geometry · Computer Science 2016-10-04 Sayan Bandyapadhyay , Aritra Banik

We develop a new numerical method for approximating the infinite time reachable set of strictly stable linear control systems. By solving a linear program with a constraint that incorporates the system dynamics, we compute a polytope with…

Optimization and Control · Mathematics 2019-04-03 Andreas Ernst , Lars Grüne , Janosch Rieger

A new class of projected dynamical systems of third order is investigated for quasi (parametric) variational inequalities in which the convex set in the classical variational inequality also depends upon the solution explicitly or…

Optimization and Control · Mathematics 2025-01-10 Oday Hazaimah

The ``losing positions" of certain combinatorial games constitute linear error detecting and correcting codes. We show that a large class of games that can be cast in the form of *annihilation games*, provides a potentially polynomial…

Combinatorics · Mathematics 2016-09-06 Aviezri S. Fraenkel

We consider problems with multiple linear objectives and linear constraints and use Adjustable Robust Optimization and Polynomial Optimization as tools to approximate the Pareto set with polynomials of arbitrarily large degree. The main…

Optimization and Control · Mathematics 2015-01-13 Bram L. Gorissen , Dick den Hertog

Leadership games provide a powerful paradigm to model many real-world settings. Most literature focuses on games with a single follower who acts optimistically, breaking ties in favour of the leader. Unfortunately, for real-world…

Artificial Intelligence · Computer Science 2018-08-01 Giuseppe De Nittis , Alberto Marchesi , Nicola Gatti

Energy games belong to a class of turn-based two-player infinite-duration games}played on a weighted directed graph. It is one of the rare and intriguing combinatorial problems that lie in ${\sf NP} \cap {\sf co\mbox{-}NP}$, but are not…

Data Structures and Algorithms · Computer Science 2018-03-02 Krishnendu Chatterjee , Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

In order to verify programs or hybrid systems, one often needs to prove that certain formulas are unsatisfiable. In this paper, we consider conjunctions of polynomial inequalities over the reals. Classical algorithms for deciding these not…

Numerical Analysis · Mathematics 2009-02-02 David Monniaux

Convexification is a core technique in global polynomial optimization. Currently, there are two main approaches competing in theory and practice: the approach of nonlinear programming and the approach based on positivity certificates from…

Optimization and Control · Mathematics 2021-09-29 Gennadiy Averkov , Benjamin Peters , Sebastian Sager
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