2019-06-18|访问量:|[返回]
Machine Learning Theory Workshop
TIME: June 20-21, 2019
LOCATION: Lecture Hall, Jiayibing Building, Jingchunyuan 82, Peking University
Description
Over the last few years, tremendous progress has been made in machine learning, in terms of both applications and algorithms. At the same time, there also have been a number of novel works on theoretical understandings for different learning problems and algorithms, but many challenges still remain. The goal of this workshop is to study the challenges in machine learning theory, especially to foster discussion and spur research between experts and researchers in the field that can solve fundamental problems, as well as to promote academic communication and cooperation between faculties and students from Peking University and overseas outstanding scholars.
Scientific Committee
Weinan E (Princeton University)
Wen Gao (Peking University)
Pingwen Zhang (Peking University)
Organization Committee
Bin Dong (Peking University)
Liwei Wang (Peking University)
Zhihua Zhang (Peking University)
Invited Speaker
Stephen Boyd (Stanford University)
Simon Du (Princeton University)
Quanquan Gu (University of California, Los Angeles)
Wei Hu (Princeton University)
Nan Jiang (University of Illinois at Urbana-Champaign)
Qianxiao Li (Institute of High Performance Computing, Singapore)
Ruoyu Sun (University of Illinois at Urbana-Champaign)
Yuhao Wang (Massachusetts Institute of Technology)
Huan Xu (Georgia Institute of Technology)
Qi Yu (Northeastern University)
Schedule
2nd Machine Learning Theory Workshop
June 20 |
Title |
Speaker |
9:00-10:00 Keynote |
TBA |
Stephen Boyd (Stanford) |
Break |
||
10:15-11:00 |
Sample-efficient exploration in reinforcement learning with function approximation |
Nan Jiang (UIUC) |
11:00-11:45 |
Continuous-time methods for stochastic optimization and batch normalization |
Qianxiao Li (HPC) |
11:45-1:30 |
Lunch |
|
1:30-2:15 |
Physics Guided Deep Learning for Large-Scale Spatiotemporal Analysis |
Rose Yu (NEU) |
2:15-3:00 |
Towards Understanding Overparameterized Deep Neural Networks: From Optimization To Generalization |
Quanquan Gu (UCLA) |
Break |
||
3:15-4:00 |
Learning High-Dimensional Graphical Models under Total Positivity without Tuning Parameters |
Yuhao Wang (MIT) |
4:00-4:45 |
On the connection between over-parameterized neural networks and kernels, and how to make that useful |
Wei Hu (Princeton) |
Break |
||
5:00-5:20 |
Appropriate function spaces for two-layer neural network and residual network models |
Chao Ma (Princeton) |
5:20-5:40 |
A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning |
Xiang Li (PKU student) |
5:40-6:00 |
Distributed Bandit Learning: Near-Optimal Regret with Efficient Communication |
Yuanhao Wang (THU student) |
6:30 |
Banquet |
|
June 21 |
Title |
Speaker |
9:00-9:45 |
Title: The online saddle point problem and its applications |
Huan Xu (Georgia Tech) |
9:45-10:30 |
Towards Deeper Understanding of Neural Network Landscape: Local Minima and Decreasing Paths |
Ruoyu Sun (UIUC) |
Break |
||
10:45-11:30 |
Provably Efficient Reinforcement Learning with Function Approximation |
Simon Du (Princeton) |
11:30-11:50 |
A Priori Estimates of Generalization Error for Two-layer and Residual Networks |
Lei Wu (Princeton) |
11:50-12:10 |
A Gram-Gauss-Newton Method Learning Over-parameterized Deep Neural Networks for Regression Problems |
Tianle Cai (PKU student) |
12:10-2:00 |
Lunch |
|
Accommodation and Travel Information
Invited speakers will stay in No.9 building of "Zhong Guan Xin Yuan" Hotel. By default, rooms have been booked for the arrival on June 19 and departure on June 22. The hotel is across the street of Peking University Campus, about 15-20 minutes' walk to the Lecture Hall.
PKU will cover travel expenses for all the speakers.
Other participants are responsible for arranging and paying for their own reservations for hotel accommodations and travel expenses. If anyone needs help, please contact Ms. Yanyun Liu.
Hotel Address: “Zhong Guan Xin Yuan” Hotel (Zhongguanyuan Global Village)
No. 126 Zhongguancun North Road, Haidian District, Beijing 100871, China
Tel: + (86 10) 62752288
Fax: + (86 10) 62752236
From the Airport to the Hotel: The most convenient way to get the hotel from the airport is to take a taxi. It costs about RMB 120 yuans. You are also responsible to pay the toll of 10 yuans. So you need some pocket money. A possible way to get cash is to find an ATM in the lobby of the airport. You may print this slip and show it to the taxi driver.
Contact
Mailing address: Yanyun Liu
Room 1266, Science Building No .1, Peking University, Beijing, China 100871
Phone: +86 10 62768630
E-mail: yyliu@pku.edu.cn
Fax:+ (86 10) 62751801
Tips
Gmail account is NOT accessible in China. If you get used to gmail account, please prepare for an alternative email account. Google, Tweeter, Facebook, Youtube etc are not available.
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