Search Results for author: Panagiotis Patrinos

Found 14 papers, 10 papers with code

Block Alternating Bregman Majorization Minimization with Extrapolation

1 code implementation9 Jul 2021 Le Thi Khanh Hien, Duy Nhat Phan, Nicolas Gillis, Masoud Ahookhosh, Panagiotis Patrinos

In this paper, we consider a class of nonsmooth nonconvex optimization problems whose objective is the sum of a block relative smooth function and a proper and lower semicontinuous block separable function.

Lasry-Lions Envelopes and Nonconvex Optimization: A Homotopy Approach

no code implementations15 Mar 2021 Miguel Simões, Andreas Themelis, Panagiotis Patrinos

Lasry-Lions envelopes can also be seen as an "intermediate" between a given function and its convex envelope, and we make use of this property to develop a method that builds a sequence of approximate subproblems that are easier to solve than the original problem.

Data-driven distributionally robust MPC for constrained stochastic systems

no code implementations4 Mar 2021 Peter Coppens, Panagiotis Patrinos

In this paper we introduce a novel approach to distributionally robust optimal control that supports online learning of the ambiguity set, while guaranteeing recursive feasibility.

Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel Machine

1 code implementation16 Feb 2021 Francesco Tonin, Arun Pandey, Panagiotis Patrinos, Johan A. K. Suykens

Detecting out-of-distribution (OOD) samples is an essential requirement for the deployment of machine learning systems in the real world.

Out-of-Distribution Detection

Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints

no code implementations25 Nov 2020 Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens

We introduce Constr-DRKM, a deep kernel method for the unsupervised learning of disentangled data representations.

QPALM: A Proximal Augmented Lagrangian Method for Nonconvex Quadratic Programs

1 code implementation6 Oct 2020 Ben Hermans, Andreas Themelis, Panagiotis Patrinos

The resulting implementation is shown to be extremely robust in numerical simulations, solving all of the Maros-Meszaros problems and finding a stationary point for most of the nonconvex QPs in the Cutest test set.

Optimization and Control 90C05, 90C20, 90C26, 49J53, 49M15

Douglas-Rachford splitting and ADMM for nonconvex optimization: Accelerated and Newton-type linesearch algorithms

3 code implementations20 May 2020 Andreas Themelis, Lorenzo Stella, Panagiotis Patrinos

Although the performance of popular optimization algorithms such as Douglas-Rachford splitting (DRS) and the ADMM is satisfactory in small and well-scaled problems, ill conditioning and problem size pose a severe obstacle to their reliable employment.

Optimization and Control 90C06, 90C25, 90C26, 49J52, 49J53

Multi-block Bregman proximal alternating linearized minimization and its application to orthogonal nonnegative matrix factorization

1 code implementation4 Aug 2019 Masoud Ahookhosh, Le Thi Khanh Hien, Nicolas Gillis, Panagiotis Patrinos

We introduce and analyze BPALM and A-BPALM, two multi-block proximal alternating linearized minimization algorithms using Bregman distances for solving structured nonconvex problems.

Optimization and Control Numerical Analysis Numerical Analysis

Block-coordinate and incremental aggregated proximal gradient methods for nonsmooth nonconvex problems

2 code implementations24 Jun 2019 Puya Latafat, Andreas Themelis, Panagiotis Patrinos

This paper analyzes block-coordinate proximal gradient methods for minimizing the sum of a separable smooth function and a (nonseparable) nonsmooth function, both of which are allowed to be nonconvex.

Optimization and Control 90C06, 90C25, 90C26, 49J52, 49J53

Bregman forward-backward splitting for nonconvex composite optimization: superlinear convergence to nonisolated critical points

1 code implementation28 May 2019 Masoud Ahookhosh, Andreas Themelis, Panagiotis Patrinos

We introduce Bella, a locally superlinearly convergent Bregman forward-backward splitting method for minimizing the sum of two nonconvex functions, one of which satisfying a relative smoothness condition and the other one possibly nonsmooth.

Optimization and Control 90C06, 90C25, 90C26, 49J52, 49J53

Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization

no code implementations ICML 2020 Le Thi Khanh Hien, Nicolas Gillis, Panagiotis Patrinos

We propose inertial versions of block coordinate descent methods for solving non-convex non-smooth composite optimization problems.

SuperMann: a superlinearly convergent algorithm for finding fixed points of nonexpansive operators

1 code implementation22 Sep 2016 Andreas Themelis, Panagiotis Patrinos

As a result, SuperMann enhances and robustifies all operator splitting schemes for structured convex optimization, overcoming their well known sensitivity to ill conditioning.

Optimization and Control 47H09, 90C25, 90C53, 65K15

Forward-backward envelope for the sum of two nonconvex functions: Further properties and nonmonotone line-search algorithms

4 code implementations20 Jun 2016 Andreas Themelis, Lorenzo Stella, Panagiotis Patrinos

Extending previous results we show that, despite being nonsmooth for fully nonconvex problems, the FBE still enjoys favorable first- and second-order properties which are key for the convergence results of ZeroFPR.

Optimization and Control 90C06, 90C25, 90C26, 90C53, 49J52, 49J53

Forward-backward quasi-Newton methods for nonsmooth optimization problems

1 code implementation27 Apr 2016 Lorenzo Stella, Andreas Themelis, Panagiotis Patrinos

We propose an algorithmic scheme that enjoys the same global convergence properties of FBS when the problem is convex, or when the objective function possesses the Kurdyka-{\L}ojasiewicz property at its critical points.

Optimization and Control

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