1 citations · 3 across the 7 of their papers we have counts for
7 papers
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
Shuyao Li, Yu Cheng, Ilias Diakonikolas +3
Finding an approximate second-order stationary point (SOSP) is a well-studied and fundamental problem in stochastic nonconvex optimization with many applications in machine learnin…
Robustly Learning Single-Index Models via Alignment Sharpness
Nikos Zarifis, Puqian Wang, Ilias Diakonikolas +1
We study the problem of learning Single-Index Models under the loss in the agnostic model. We give an efficient learning algorithm, achieving a constant factor approximatio…
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions
Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas
Machine learning approaches relying on such criteria as adversarial robustness or multi-agent settings have raised the need for solving game-theoretic equilibrium problems. Of part…
Block-Coordinate Methods and Restarting for Solving Extensive-Form Games
Darshan Chakrabarti, Jelena Diakonikolas, Christian Kroer
Coordinate descent methods are popular in machine learning and optimization for their simple sparse updates and excellent practical performance. In the context of large-scale seque…
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane +2
We study the problem of learning general (i.e., not necessarily homogeneous) halfspaces with Random Classification Noise under the Gaussian distribution. We establish nearly-matchi…
Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization
Cheuk Yin Lin, Chaobing Song, Jelena Diakonikolas
Exploiting partial first-order information in a cyclic way is arguably the most natural strategy to obtain scalable first-order methods. However, despite their wide use in practice…