Publications associées à Basic gestalt laws cannot explain uncrowding

BENIGN LANDSCAPES OF LOW-DIMENSIONAL RELAXATIONS FOR ORTHOGONAL SYNCHRONIZATION ON GENERAL GRAPHS

Orthogonal group synchronization is the problem of estimating n elements Z(1),& mldr;,Z(n) from the rxr orthogonal group given some relative measurements R-ij approximate to Z(i)Z(j)(-1). The least-squares formulation is nonconvex. To avoid its local minim ...

Siam Publications2024

Stability: a search for structure

Wouter Jongeneel

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

EPFL2024

Specific Gestalt principles cannot explain (un)crowding

Michael Herzog, Oh-Hyeon Choung, Einat Rashal

The standard physiological model has serious problems accounting for many aspects of vision, particularly when stimulus configurations become slightly more complex than the ones classically used, e.g., configurations of Gabors rather than only one or a few ...

2023

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Rachid Guerraoui, Nirupam Gupta, Rafaël Benjamin Pinot, Youssef Allouah, Geovani Rizk

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

2023

A Least-Squares Method for the Solution of the Non-smooth Prescribed Jacobian Equation

Alexandre Caboussat, Dimitrios Gourzoulidis

We consider a least-squares/relaxation finite element method for the numerical solution of the prescribed Jacobian equation. We look for its solution via a least-squares approach. We introduce a relaxation algorithm that decouples this least-squares proble ...

SPRINGER/PLENUM PUBLISHERS2022

Rapid Scalable Distributed Power Flow with Open-Source Implementation

Yuning Jiang, Xinliang Dai

This paper introduces a new method for solving the distributed AC power flow (PF) problem by further exploiting the problem formulation. We propose a new variant of the ALADIN algorithm devised specifically for this type of problem. This new variant is cha ...

ELSEVIER2022

Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem

Nirupam Gupta

This paper considers the multi-agent linear least-squares problem in a server-agent network architecture. The system comprises multiple agents, each with a set of local data points. The agents are connected to a server, and there is no inter-agent communic ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Frequency-Domain Diffusion Adaptation Over Networks

Ali H. Sayed, Ricardo Merched, Shuo Zhang

This paper analyzes the implementation of least-mean-squares (LMS)-based, adaptive diffusion algorithms over networks in the frequency-domain (FD). We focus on a scenario of noisy links and include a moving-average step for denoising after self-learning to ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Last iterate convergence of SGD for Least-Squares in the Interpolation regime

Aditya Vardhan Varre, Nicolas Henri Bernard Flammarion, Loucas Pillaud-Vivien

Motivated by the recent successes of neural networks that have the ability to fit the data perfectly \emph{and} generalize well, we study the noiseless model in the fundamental least-squares setup. We assume that an optimum predictor fits perfectly inputs ...

Advances in Neural Information Processing Systems 20212021

Eigendecomposition-Free Training of Deep Networks for Linear Least-Square Problems

Pascal Fua, Mathieu Salzmann, Fei Wang, Kwang Moo Yi, Zheng Dang, Yinlin Hu

Many classical Computer Vision problems, such as essential matrix computation and pose estimation from 3D to 2D correspondences, can be tackled by solving a linear least-square problem, which can be done by finding the eigenvector corresponding to the smal ...

IEEE COMPUTER SOC2021

Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections

Volkan Cevher, Junhong Lin

We study the least-squares regression problem over a Hilbert space, covering nonparametric regression over a reproducing kernel Hilbert space as a special case. We rst investigate regularized algorithms adapted to a projection operator on a closed subspace ...

2020

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces

Volkan Cevher, Junhong Lin

We investigate regularized algorithms combining with projection for least-squares regression problem over a Hilbert space, covering nonparametric regression over a reproducing kernel Hilbert space. We prove convergence results with respect to variants of n ...

ICML2018

Optimal Rates for Spectral Algorithms with Least-Squares Regression over Hilbert Spaces

Volkan Cevher, Junhong Lin

In this paper, we study regression problems over a separable Hilbert space with the square loss, covering non-parametric regression over a reproducing kernel Hilbert space. We investigate a class of spectral/regularized algorithms, including ridge regressi ...

2020

The effect of overall stimulus configuration on crowding

Michael Herzog, Maya Roinishvili, Mattew Pachai

The standard framework to study vision is typically hierarchical and feedforward, which facilitates deconstructing complex mechanisms into smaller, more tractable problems. However, this framework can fail when elements are presented in context, as they ar ...

2017

ALS Scheme using Extent-based Constraints for the Analysis of Chemical Reaction Systems

Michael Amrhein, Dominique Bonvin, Julien Léo Billeter

Multivariate curve resolution via alternating least squares (ALS) is used to resolve the concentration profiles C and the pure component spectra E of S species from the multivariate absorbance data A, assuming the bilinear model ...

2016

What crowding can tell us about object representations

Michael Herzog, Mauro Manassi, Aaron Michael Clarke

In crowding, perception of a target usually deteriorates when flanking elements are presented next to the target. Surprisingly, adding further flankers can lead to a release from crowding. In previous work we showed that, for example, vernier offset discri ...

Association for Research in Vision and Ophthalmology (ARVO)2016

Discrete least squares polynomial approximation with random evaluations − application to parametric and stochastic elliptic PDEs

Fabio Nobile, Giovanni Migliorati

Motivated by the numerical treatment of parametric and stochastic PDEs, we analyze the least-squares method for polynomial approximation of multivariate functions based on random sampling according to a given probability measure. Recent work has shown that ...

2015

A reduced computational and geometrical framework for inverse problems in haemodynamics

Alfio Quarteroni, Gianluigi Rozza, Toni Mikael Lassila, Andrea Manzoni

The solution of inverse problems in cardiovascular mathematics is computationally expensive. In this paper we apply a domain parametrization technique to reduce both the geometrical and computational complexity of the forward problem, and replace the finit ...

Wiley-Blackwell2013

Randomized Extended Kaczmarz For Solving Least Squares

Nikolaos Freris

We present a randomized iterative algorithm that exponentially converges in the mean square to the minimum l(2)-norm least squares solution of a given linear system of equations. The expected number of arithmetic operations required to obtain an estimate o ...

Society for Industrial and Applied Mathematics2013

Wavelet Shrinkage With Consistent Cycle Spinning Generalizes Total Variation Denoising

Michaël Unser, Ulugbek Kamilov, Emrah Bostan

We introduce a new wavelet-based method for the implementation of Total-Variation-type denoising. The data term is least-squares, while the regularization term is gradient-based. The particularity of our method is to exploit a link between the discrete gra ...

IEEE Institute of Electrical and Electronics Engineers2012