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Poster
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Thu 14:00
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Stochastic Chebyshev Gradient Descent for Spectral Optimization
Insu Han · Haim Avron · Jinwoo Shin
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Poster
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Thu 14:00
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Bipartite Stochastic Block Models with Tiny Clusters
Stefan Neumann
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Poster
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Wed 7:45
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ℓ1-regression with Heavy-tailed Distributions
Lijun Zhang · Zhi-Hua Zhou
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Poster
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Thu 14:00
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Optimal Subsampling with Influence Functions
Daniel Ting · Eric Brochu
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Poster
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Wed 14:00
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Stochastic Nonparametric Event-Tensor Decomposition
Shandian Zhe · Yishuai Du
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Poster
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Thu 14:00
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Adaptive Learning with Unknown Information Flows
Yonatan Gur · Ahmadreza Momeni
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Poster
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Thu 7:45
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Reparameterization Gradient for Non-differentiable Models
Wonyeol Lee · Hangyeol Yu · Hongseok Yang
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Poster
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Thu 7:45
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A Model for Learned Bloom Filters and Optimizing by Sandwiching
Michael Mitzenmacher
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Spotlight
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Thu 12:30
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A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization
Zhize Li · Jian Li
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Poster
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Thu 14:00
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Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters
Pavel Dvurechenskii · Darina Dvinskikh · Alexander Gasnikov · Cesar Uribe · Angelia Nedich
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Poster
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Wed 14:00
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Proximal Graphical Event Models
Debarun Bhattacharjya · Dharmashankar Subramanian · Tian Gao
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Poster
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Thu 14:00
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How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD
Zeyuan Allen-Zhu
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