Papers
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization
Rong Ge, Zhize Li, Weiyao Wang et al.
Near Optimal Methods for Minimizing Convex Functions with Lipschitz p-th Derivatives
Alexander Gasnikov, Pavel Dvurechensky, Eduard Gorbunov et al.
Optimal Tensor Methods in Smooth Convex and Uniformly ConvexOptimization
Alexander Gasnikov, Pavel Dvurechensky, Eduard Gorbunov et al.
Statistical Learning with a Nuisance Component
Dylan J. Foster, Vasilis Syrgkanis
The Complexity of Making the Gradient Small in Stochastic Convex Optimization
Dylan J. Foster, Ayush Sekhari, Ohad Shamir et al.
Sum-of-squares meets square loss: Fast rates for agnostic tensor completion
Dylan J. Foster, Andrej Risteski
High probability generalization bounds for uniformly stable algorithms with nearly optimal rate
Vitaly Feldman, Jan Vondrak
Achieving the Bayes Error Rate in Stochastic Block Model by SDP, Robustly
Yingjie Fei, Yudong Chen
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points
Cong Fang, Zhouchen Lin, Tong Zhang
Lower Bounds for Locally Private Estimation via Communication Complexity
John Duchi, Ryan Rogers
Lower Bounds for Parallel and Randomized Convex Optimization
Jelena Diakonikolas, Cristóbal Guzmán
Testing Identity of Multidimensional Histograms
Ilias Diakonikolas, Daniel M. Kane, John Peebles
Communication and Memory Efficient Testing of Discrete Distributions
Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane et al.
Minimax experimental design: Bridging the gap between statistical and worst-case approaches to least squares regression
Michał Dereziński, Kenneth L. Clarkson, Michael W. Mahoney et al.
Computational Limitations in Robust Classification and Win-Win Results
Akshay Degwekar, Preetum Nakkiran, Vinod Vaikuntanathan
Is your function low dimensional?
Anindya De, Elchanan Mossel, Joe Neeman
Reconstructing Trees from Traces
Sami Davies, Miklos Z. Racz, Cyrus Rashtchian
Computationally and Statistically Efficient Truncated Regression
Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos et al.
Space lower bounds for linear prediction in the streaming model
Yuval Dagan, Gil Kur, Ohad Shamir
Learning from Weakly Dependent Data under Dobrushin’s Condition
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala et al.
Combining Online Learning Guarantees
Ashok Cutkosky
A near-optimal algorithm for approximating the John Ellipsoid
Michael B. Cohen, Ben Cousins, Yin Tat Lee et al.