Publications related to Sequence transformation

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit

Ursula Röthlisberger, Justin Villard, Martin Peter Bircher

Second-order Moller-Plesset perturbation theory (MP2) is the most expedient wave function-based method for considering electron correlation in quantum chemical calculations and, as such, provides a cost-effective framework to assess the effects of basis se ...

Washington2023

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization

Volkan Cevher, Alp Yurtsever, Maria-Luiza Vladarean

We propose a stochastic conditional gradient method (CGM) for minimizing convex finitesum objectives formed as a sum of smooth and non-smooth terms. Existing CGM variants for this template either suffer from slow convergence rates, or require carefully inc ...

2022

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

Nirupam Gupta

This article considers solving an overdetermined system of linear equations in peer-to-peer multiagent networks. The network is assumed to be synchronous and strongly connected. Each agent has a set of local data points, and their goal is to compute a line ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

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

Multiagent Fully Decentralized Value Function Learning With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Lucas Cesar Eduardo Cassano

This article develops a fully decentralized multiagent algorithm for policy evaluation. The proposed scheme can be applied to two distinct scenarios. In the first scenario, a collection of agents have distinct datasets gathered by following different behav ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Optimal Control Combining Emulation and Imitation to Acquire Physical Assistance Skills

Sylvain Calinon, Amirreza Razmjoo Fard, Teguh Santoso Lembono

paper studies exploiting action-level learning (imitation) in the optimal control problem context. Cost functions defined by the optimal control methods are similar to the goal-level learning (emulation) in animals. However, imitating the robot's or others ...

IEEE2021

Sub‐asymptotic motivation for new conditional multivariate extreme models

Anthony Christopher Davison, Thomas Lugrin, Jonathan A. Tawn

Statistical models for extreme values are generally derived from non-degenerate probabilistic limits that can be used to approximate the distribution of events that exceed a selected high threshold. If convergence to the limit distribution is slow, then th ...

2021

On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent

Nicolas Henri Bernard Flammarion, Scott William Pesme, Aymeric Daphnis Kévin Dieuleveut

Constant step-size Stochastic Gradient Descent exhibits two phases: a transient phase during which iterates make fast progress towards the optimum, followed by a stationary phase during which iterates oscillate around the optimal point. In this paper, we s ...

2020

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Sequence transformation

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Multiagent Fully Decentralized Value Function Learning With Linear Convergence Rates

Optimal Control Combining Emulation and Imitation to Acquire Physical Assistance Skills

Sub‐asymptotic motivation for new conditional multivariate extreme models

On the Stability of FDTD-Based Numerical Codes to Evaluate Lightning-Induced Overvoltages in Overhead Transmission Lines

On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent

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On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

Sub‐asymptotic motivation for new conditional multivariate extreme models

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Multiagent Fully Decentralized Value Function Learning With Linear Convergence Rates

On the Stability of FDTD-Based Numerical Codes to Evaluate Lightning-Induced Overvoltages in Overhead Transmission Lines

On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit

Optimal Control Combining Emulation and Imitation to Acquire Physical Assistance Skills