Chris Junchi Li

According to our database1, Chris Junchi Li authored at least 16 papers between 2016 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2020
ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm.
CoRR, 2020

Stochastic Modified Equations for Continuous Limit of Stochastic ADMM.
CoRR, 2020

On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration.
Proceedings of the Conference on Learning Theory, 2020

2019
Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Differential Inclusions for Modeling Nonsmooth ADMM Variants: A Continuous Limit Theory.
Proceedings of the 36th International Conference on Machine Learning, 2019

On the Global Convergence of Continuous-Time Stochastic Heavy-Ball Method for Nonconvex Optimization.
Proceedings of the 2019 IEEE International Conference on Big Data (Big Data), 2019

2018
Near-optimal stochastic approximation for online principal component estimation.
Math. Program., 2018

Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack.
CoRR, 2018

Diffusion Approximations for Online Principal Component Estimation and Global Convergence.
CoRR, 2018

SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Statistical Sparse Online Regression: A Diffusion Approximation Perspective.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Batch Size Matters: A Diffusion Approximation Framework on Nonconvex Stochastic Gradient Descent.
CoRR, 2017

Online Multiview Representation Learning: Dropping Convexity for Better Efficiency.
CoRR, 2017

Diffusion Approximations for Online Principal Component Estimation and Global Convergence.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016


  Loading...