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05/22/2023
Fast Convergence in Learning Two-Layer Neural Networks with Separable Data
Normalized gradient descent has shown substantial success in speeding up...
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02/18/2023
Generalization and Stability of Interpolating Neural Networks with Minimal Width
We investigate the generalization and optimization of k-homogeneous shal...
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09/15/2022
Decentralized Learning with Separable Data: Generalization and Fast Algorithms
Decentralized learning offers privacy and communication efficiency when ...
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10/26/2020
Asymptotic Behavior of Adversarial Training in Binary Classification
It is widely known that several machine learning models are susceptible ...
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06/16/2020
Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions
Empirical Risk Minimization (ERM) algorithms are widely used in a variet...
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02/23/2020
Quantized Push-sum for Gossip and Decentralized Optimization over Directed Graphs
We consider a decentralized stochastic learning problem where data point...
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02/17/2020
Sharp Asymptotics and Optimal Performance for Inference in Binary Models
We study convex empirical risk minimization for high-dimensional inferen...
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08/12/2019
Sharp Guarantees for Solving Random Equations with One-Bit Information
We study the performance of a wide class of convex optimization-based es...
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07/24/2019