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

Readme

I will be joining Google Brain as a research scientist in the fall of 2018.

I completed my Ph.D. 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, meta-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.

Professional Activities

Reviewer, International Conference on Machine Learning (ICML), 2016, 2017, 2018.
Reviewer, Advances in Neural Information Processing Systems (NIPS), 2016, 2017, 2018.
Reviewer, International Conference on Learning Representations (ICLR), 2019.
Reviewer, AAAI Conference on Artificial Intelligence (AAAI), 2017, 2018, 2019.
Reviewer, Neural Computation.

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 Friday 5th October, 2018 by TEX4ht.
Copyright  2018 Hanxiao Liu. All Rights Reserved.