
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization
We consider the task of decentralized minimization of the sum of smooth ...
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A NonAsymptotic Analysis for Stein Variational Gradient Descent
We study the Stein Variational Gradient Descent (SVGD) algorithm, which ...
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Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm
We consider the task of sampling with respect to a log concave probabili...
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Dualize, Split, Randomize: Fast Nonsmooth Optimization Algorithms
We introduce a new primaldual algorithm for minimizing the sum of three...
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Wasserstein Proximal Gradient
We consider the task of sampling from a logconcave probability distribu...
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Distributed Fixed Point Methods with Compressed Iterates
We propose basic and natural assumptions under which iterative optimizat...
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Maximum Mean Discrepancy Gradient Flow
We construct a Wasserstein gradient flow of the maximum mean discrepancy...
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Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates
We propose a new algorithmStochastic Proximal Langevin Algorithm (SPL...
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A Fully Stochastic PrimalDual Algorithm
A new stochastic primaldual algorithm for solving a composite optimizat...
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A Constant Step Stochastic DouglasRachford Algorithm with Application to Non Separable Regularizations
The Douglas Rachford algorithm is an algorithm that converges to a minim...
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Snake: a Stochastic Proximal Gradient Algorithm for Regularized Problems over Large Graphs
A regularized optimization problem over a large unstructured graph is st...
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Adil Salim
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