Publications related to Topologies on spaces of linear maps

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Volkan Cevher, Grigorios Chrysos, Fanghui Liu

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

2024

Mapping orthorhombic domains with geometrical phase analysis in rare-earth nickelate heterostructures

Duncan Thomas Lindsay Alexander, Bernat Mundet, Jean-Marc Triscone

Most perovskite oxides belong to the Pbnm space group, composed of an anisotropic unit cell, A-site antipolar displacements, and oxygen octahedral tilts. Mapping the orientation of the orthorhombic unit cell in epitaxial heterostructures that consist of at ...

Melville2024

Decentralized learning made easy with DecentralizePy

Anne-Marie Kermarrec, Rafael Pereira Pires, Akash Balasaheb Dhasade, Rishi Sharma, Milos Vujasinovic

Decentralized learning (DL) has gained prominence for its potential benefits in terms of scalability, privacy, and fault tolerance. It consists of many nodes that coordinate without a central server and exchange millions of parameters in the inherently ite ...

2023

Discrete Voss surfaces: Designing geodesic gridshells with planar cladding panels

Corentin Jean Dominique Fivet, Nicolas Robin Montagne, Olivier Baverel

The design and construction of doubly-curved structures often reveals to be challenging and can result in complex manufacturing and assembly. A recent strategy to tackle this difficulty consists in exploiting the connection between discrete differential ge ...

2022

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient

Volkan Cevher, Ahmet Alacaoglu

In this paper, we analyze the recently proposed stochastic primal-dual hybrid gradient (SPDHG) algorithm and provide new theoretical results. In particular, we prove almost sure convergence of the iterates to a solution with convexity and linear convergenc ...

SIAM PUBLICATIONS2022

Accelerated SGD for Non-Strongly-Convex Least Squares

Nicolas Henri Bernard Flammarion, Aditya Vardhan Varre

We consider stochastic approximation for the least squares regression problem in the non-strongly convex setting. We present the first practical algorithm that achieves the optimal prediction error rates in terms of dependence on the noise of the problem, ...

2022

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Sulaiman A S A E Alghunaim

This article studies a class of nonsmooth decentralized multiagent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a common nonsmooth term. We propose a general primal-dual algorithmic framewor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Variance-Reduced Stochastic Learning Under Random Reshuffling

Ali H. Sayed, Bicheng Ying, Kun Yuan

Several useful variance-reduced stochastic gradient algorithms, such as SVRG, SAGA, Finito, and SAG, have been proposed to minimize empirical risks with linear convergence properties to the exact minimizer. The existing convergence results assume uniform d ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

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Topologies on spaces of linear maps

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Mapping orthorhombic domains with geometrical phase analysis in rare-earth nickelate heterostructures

Decentralized learning made easy with DecentralizePy

Discrete Voss surfaces: Designing geodesic gridshells with planar cladding panels

Preconditioners for robust optimal control problems under uncertainty

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient

Accelerated SGD for Non-Strongly-Convex Least Squares

On Katznelson's Question for skew product systems

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Variance-Reduced Stochastic Learning Under Random Reshuffling

Graph Chatbot

Chat with Graph Search

Preconditioners for robust optimal control problems under uncertainty

Discrete Voss surfaces: Designing geodesic gridshells with planar cladding panels

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Decentralized learning made easy with DecentralizePy

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Mapping orthorhombic domains with geometrical phase analysis in rare-earth nickelate heterostructures

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient

Accelerated SGD for Non-Strongly-Convex Least Squares

On Katznelson's Question for skew product systems

Variance-Reduced Stochastic Learning Under Random Reshuffling