Hanxiao Liu
PIC
6227 Gates-Hillman Center   
Carnegie Mellon University
PIC

Readme

I’m a Ph.D. candidate in the Language Technologies Institute, School of Computer Science at Carnegie Mellon University, working with Professor Yiming Yang. Prior to that, I received my B.E. from Department of Automation at Tsinghua University in 2013.

My research interests include deep learning, reinforcement learning and language understanding. Recently, I’m working on the automatic design of neural architectures.

Work Experience

Publications

“*” indicates equal contribution. Co-first authors are ordered alphabetically.

Preprints

Professional Service

Reviewer, ICML 2018, NIPS 2018.
Reviewer, ICML 2017, NIPS 2017, AAAI 2017, Neural Computation.
Reviewer, ICML 2016, NIPS 2016.

Notes & Lectures

1.
Reinforcement Learning, Basics
2.
Reinforcement Learning, Policy Optimization
3.
Adversarial Examples
4.
Rademacher Complexity and VC Dimension
5.
Generative Adversarial Networks
6.
Spectral Analysis of Stationary Stochastic Process
7.
Screening Tests for the Lasso
8.
Large-Scale Stochastic Optimization
9.
Adaptive Stochastic Subgradient Methods
10.
Variational Inference for Bayes von Mises-Fisher Mixture
11.
The EM algorithm and Variational Bayes
12.
Spectral Algorithms

Last compiled on Saturday 21st April, 2018 by TEX4ht.
Copyright  2018 Hanxiao Liu. All Rights Reserved.