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Alternating Minimization is a widely used and empirically successful heuristic for matrix completion and related low-rank optimization problems. Theoretical guarantees for Alternating Minimization have been hard to come by and are still…

Machine Learning · Computer Science 2014-05-15 Moritz Hardt

This paper develops a new exponential forgetting algorithm that can prevent so-called the estimator windup problem, while retaining fast convergence speed. To investigate the properties of the proposed forgetting algorithm, boundedness of…

Systems and Control · Electrical Eng. & Systems 2020-04-09 Hyo-Sang Shin , Hae-In Lee

In this paper, we introduce the Maximum Matrix Contraction problem, where we aim to contract as much as possible a binary matrix in order to maximize its density. We study the complexity and the polynomial approximability of the problem.…

Computational Complexity · Computer Science 2023-06-05 Dimitri Watel , Pierre-Louis Poirion

Computing the probability of a formula given the probabilities or weights associated with other formulas is a natural extension of logical inference to the probabilistic setting. Surprisingly, this problem has received little attention in…

Artificial Intelligence · Computer Science 2012-03-19 Vibhav Gogate , Pedro Domingos

A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP-EM algorithm. A dual mathematical interpretation of the…

Computer Vision and Pattern Recognition · Computer Science 2010-06-16 Guoshen Yu , Guillermo Sapiro , Stéphane Mallat

Binary observations are often repeated to improve data quality, creating technical replicates. Several scoring methods are commonly used to infer the actual individual state and obtain a probability for each state. The common practice of…

Methodology · Statistics 2025-01-24 Manuela Royer-Carenzi , Hadrien Lorenzo , Pierre Pudlo

Learning Automata (LA) are considered as one of the most powerful tools in the field of reinforcement learning. The family of estimator algorithms is proposed to improve the convergence rate of LA and has made great achievements. However,…

Artificial Intelligence · Computer Science 2017-12-04 Chong Di

The bilinear assignment problem (BAP) is a generalization of the well-known quadratic assignment problem (QAP). In this paper, we study the problem from the computational analysis point of view. Several classes of neigborhood structures are…

Data Structures and Algorithms · Computer Science 2017-09-12 Vladyslav Sokol , Ante Ćustić , Abraham P. Punnen , Binay Bhattacharya

Nowadays, fast delivery services have created the need for high-density warehouses. The puzzle-based storage system is a practical way to enhance the storage density, however, facing difficulties in the retrieval process. In this work, a…

Machine Learning · Computer Science 2022-02-09 Jing He , Xinglu Liu , Qiyao Duan , Wai Kin Victor Chan , Mingyao Qi

The problem of binary minimization of a quadratic functional in the configuration space is discussed. In order to increase the efficiency of the random-search algorithm it is proposed to change the energy functional by raising to a power…

Disordered Systems and Neural Networks · Physics 2011-09-02 Iakov Karandashev , Boris Kryzhanovsky

Studying the set of exact solutions of a system of polynomial equations largely depends on a single iterative algorithm, known as Buchberger's algorithm. Optimized versions of this algorithm are crucial for many computer algebra systems…

Machine Learning · Computer Science 2020-08-19 Dylan Peifer , Michael Stillman , Daniel Halpern-Leistner

ABC algorithms are notoriously expensive in computing time, as they require simulating many complete artificial datasets from the model. We advocate in this paper a "divide and conquer" approach to ABC, where we split the likelihood into n…

Computation · Statistics 2015-12-02 Simon Barthelmé , Nicolas Chopin , Vincent Cottet

The study proves the existence of an algorithm to receive all elements of a class of binary matrices without obtaining redundant elements, e. g. without obtaining binary matrices that do not belong to the class. This makes it possible to…

Data Structures and Algorithms · Computer Science 2013-12-03 Krasimir Yordzhev

In this paper, we present a novel algorithm to address the Network Alignment problem. It is inspired from a previous message passing framework of Bayati et al. [2] and includes several modifications designed to significantly speed up the…

Machine Learning · Computer Science 2022-01-03 Elie Mengin , Fabrice Rossi

In recent years, methods of approximate parameter estimation have attracted considerable interest in complex problems where exact likelihoods are hard to obtain. In their most basic form, Bayesian methods such as Approximate Bayesian…

Computation · Statistics 2015-07-17 Johanna Bertl , Gregory Ewing , Carolin Kosiol , Andreas Futschik

Many algorithms for data analysis exist, especially for classification problems. To solve a data analysis problem, a proper algorithm should be chosen, and also its hyperparameters should be selected. In this paper, we present a new method…

Machine Learning · Computer Science 2016-11-08 Valeria Efimova , Andrey Filchenkov , Anatoly Shalyto

We consider heuristic algorithm for solving graph isomorphism problem. The algorithm based on a successive splitting of the eigenvalues of the matrices which are modifications (to positive defined) of graphs' adjacency matrices.…

General Mathematics · Mathematics 2007-05-23 R. T. Faizullin , A. V. Prolubnikov

We study two-player general sum repeated finite games where the rewards of each player are generated from an unknown distribution. Our aim is to find the egalitarian bargaining solution (EBS) for the repeated game, which can lead to much…

Machine Learning · Computer Science 2019-06-05 Aristide Tossou , Christos Dimitrakakis , Jaroslaw Rzepecki , Katja Hofmann

We present a new approach to the electromagnetic inverse problem that explicitly addresses the ambiguity associated with its ill-posed character. Rather than calculating a single ``best'' solution according to some criterion, our approach…

Neurons and Cognition · Quantitative Biology 2007-05-23 David M. Schmidt , John S. George , C. C. Wood

A recent approach to the Beck-Fiala conjecture, a fundamental problem in combinatorics, has been to understand when random integer matrices have constant discrepancy. We give a complete answer to this question for two natural models:…

Probability · Mathematics 2021-08-17 Dylan J. Altschuler , Jonathan Niles-Weed