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Workshop
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Action Matching: A Variational Method for Learning Stochastic Dynamics from Samples
Kirill Neklyudov · Daniel Severo · Alireza Makhzani
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Workshop
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Stochastic Adaptive Regularization Method with Cubics: A High Probability Complexity Bound
Katya Scheinberg · Miaolan Xie
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Poster
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A Unified Convergence Theorem for Stochastic Optimization Methods
Xiao Li · Andre Milzarek
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Workshop
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Fri 6:30
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Efficient Second-Order Stochastic Methods for Machine Learning
Donald Goldfarb
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Workshop
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Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods
Aleksandr Beznosikov · Eduard Gorbunov · Hugo Berard · Nicolas Loizou
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Poster
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Thu 9:00
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An In-depth Study of Stochastic Backpropagation
Jun Fang · Mingze Xu · Hao Chen · Bing Shuai · Zhuowen Tu · Joseph Tighe
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Workshop
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A Stochastic Prox-Linear Method for CVaR Minimization
Si Yi Meng · Vasileios Charisopoulos · Robert Gower
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Workshop
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Stochastic Gradient Methods with Compressed Communication for Decentralized Saddle Point Problems
Chhavi Sharma · Vishnu Narayanan · Balamurugan Palaniappan
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Poster
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Tue 9:00
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Stability and Generalization for Markov Chain Stochastic Gradient Methods
Puyu Wang · Yunwen Lei · Yiming Ying · Ding-Xuan Zhou
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Poster
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Wed 9:00
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Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization
Tianyi Lin · Zeyu Zheng · Michael Jordan
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Workshop
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Fri 8:45
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PSPS: Preconditioned Stochastic Polyak Step-size method for badly scaled data
Farshed Abdukhakimov
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Poster
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Thu 14:00
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Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization
Ali Kavis · Stratis Skoulakis · Kimon Antonakopoulos · Leello Tadesse Dadi · Volkan Cevher
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