Results 21 to 30 of about 8,709 (260)
A Convex Relaxation for Weakly Supervised Classifiers [PDF]
Proceedings of the International Conference on Machine Learning (ICML), 2012 This paper introduces a general multi-class approach to weakly supervised classification. Inferring the labels and learning the parameters of the model is usually done jointly through a block-coordinate descent algorithm such as expectation-maximization (EM), which may lead to local minima.
Joulin, Armand, Bach, Francis
openaire +3 more sources
Convex Relaxations for Gas Expansion Planning [PDF]
INFORMS Journal on Computing, 2016 Expansion of natural gas networks is a critical process involving substantial capital expenditures with complex decision-support requirements. Given the nonconvex nature of gas transmission constraints, global optimality and infeasibility guarantees can only be offered by global optimisation approaches.
Conrado Borraz-Sánchez +4 more
openaire +3 more sources
Ameso optimization: A relaxation of discrete midpoint convexity [PDF]
Discrete Applied Mathematics, 2021 In this paper we introduce the Ameso optimization problem, a special class of discrete optimization problems. We establish its basic properties and investigate the relation between Ameso optimization and the convex optimization. Further, we design an algorithm to solve a multi-dimensional Ameso problem by solving a sequence of one-dimensional Ameso ...
Wen Chen +2 more
openaire +2 more sources
Entropy Minimization for Convex Relaxation Approaches [PDF]
2015 IEEE International Conference on Computer Vision (ICCV), 2015 Despite their enormous success in solving hard combinatorial problems, convex relaxation approaches often suffer from the fact that the computed solutions are far from binary and that subsequent heuristic binarization may substantially degrade the quality of computed solutions.
Mohamed Souiai +5 more
openaire +1 more source
Convex Relaxations for Isometric and Equiareal NRSfM
CoRR, 2022 Extensible objects form a challenging case for NRSfM, owing to the lack of a sufficiently constrained extensible model of the point-cloud. We tackle the challenge by proposing 1) convex relaxations of the isometric model up to quasi-isometry, and 2) convex relaxations involving the equiareal deformation model, which preserves local area and has not ...
Agniva Sengupta, Adrien Bartoli
openaire +2 more sources
Price‐based unit commitment with decision‐dependent uncertainty in hourly demand
IET Smart Grid, 2022 The price‐based unit commitment (PBUC) problem aims to optimise the power generating units' schedules to meet the system demand with the objective to maximise the generation companies' (GENCOs') profit.
Jinshun Su +2 more
doaj +1 more source
Adaptive Data-Driven Control for Linear Time Varying Systems
Machines, 2021 In this paper, we propose an adaptive data-driven control approach for linear time varying systems, affected by bounded measurement noise. The plant to be controlled is assumed to be unknown, and no information in regard to its time varying behaviour is ...
Talal Abdalla
doaj +1 more source
Direct convex relaxations of sparse SVM [PDF]
Proceedings of the 24th international conference on Machine learning, 2007 Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will in general be based on all available features in the input space. We propose two direct, novel convex relaxations of a non-convex sparse SVM formulation that explicitly ...
Antoni B. Chan +2 more
openaire +1 more source
Atomic Scheduling of Appliance Energy Consumption in Residential Smart Grids
Energies, 2019 Most of the current formulations of the optimal scheduling of appliance energy consumption use the vectors of appliances’ scheduled energy consumption over equally divided time slots of a day as optimization variables, which does not take into ...
Kyeong Soo Kim +3 more
doaj +1 more source
An accelerated primal‐dual method for semi‐definite programming relaxation of optimal power flow
IET Energy Systems Integration, 2023 The application of a semi‐definite programming (SDP) approach to the Alternating Current Optimal Power Flow problem has attracted significant attention in recent years.
Zhan Shi +6 more
doaj +1 more source