
UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization
We propose a novel adaptive, accelerated algorithm for the stochastic co...
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Adaptive Sampling for Stochastic RiskAverse Learning
We consider the problem of training machine learning models in a riskav...
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Online Variance Reduction with Mixtures
Adaptive importance sampling for stochastic optimization is a promising ...
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MultiPlayer Bandits: The Adversarial Case
We consider a setting where multiple players sequentially choose among a...
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A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise
We consider variational inequalities coming from monotone operators, a s...
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Evaluating GANs via Duality
Generative Adversarial Networks (GANs) have shown great results in accur...
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Online Adaptive Methods, Universality and Acceleration
We present a novel method for convex unconstrained optimization that, wi...
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Unsupervised Imitation Learning
We introduce a novel method to learn a policy from unsupervised demonstr...
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Faster Rates for ConvexConcave Games
We consider the use of noregret algorithms to compute equilibria for pa...
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Online Variance Reduction for Stochastic Optimization
Modern stochastic optimization methods often rely on uniform sampling wh...
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Nonmonotone Continuous DRsubmodular Maximization: Structure and Algorithms
DRsubmodular continuous functions are important objectives with wide re...
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An Online Learning Approach to Generative Adversarial Networks
We consider the problem of training generative models with a Generative ...
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Online to Offline Conversions, Universality and Adaptive Minibatch Sizes
We present an approach towards convex optimization that relies on a nove...
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k*Nearest Neighbors: From Global to Local
The weighted knearest neighbors algorithm is one of the most fundamenta...
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The Power of Normalization: Faster Evasion of Saddle Points
A commonly used heuristic in nonconvex optimization is Normalized Gradi...
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Kfir Y. Levy
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