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06/21/2023
Task-Robust Pre-Training for Worst-Case Downstream Adaptation
Pre-training has achieved remarkable success when transferred to downstr...
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05/22/2023
Policy Representation via Diffusion Probability Model for Reinforcement Learning
Popular reinforcement learning (RL) algorithms tend to produce a unimoda...
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01/29/2021
Layer-Peeled Model: Toward Understanding Well-Trained Deep Neural Networks
In this paper, we introduce the Layer-Peeled Model, a nonconvex yet anal...
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10/05/2020
Improved Analysis of Clipping Algorithms for Non-convex Optimization
Gradient clipping is commonly used in training deep neural networks part...
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03/04/2019
A Stochastic Trust Region Method for Non-convex Minimization
We target the problem of finding a local minimum in non-convex finite-su...
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02/01/2019
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points
In this paper, we prove that the simplest Stochastic Gradient Descent (S...
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12/29/2018
Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack
Zeroth-order optimization or derivative-free optimization is an importan...
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11/05/2018
Lifted Proximal Operator Machines
We propose a new optimization method for training feed-forward neural ne...
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07/04/2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator
In this paper, we propose a new technique named Stochastic Path-Integrat...
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02/27/2018
