Program


Friday, November 20, 2015: Tutorials and Workshops

Venue: Conference Hall 04-07, 2/F Lakeside 2, Hong Kong Science Park

Time Conference Hall 04 Conference Hall 05 Conference Hall 06 Conference Hall 07
08:30 Registration
09:00-10:30 Tutorial 1: A New Look at the System, Algorithm and Theory Foundations of Distributed Machine Learning (by Dr. Qirong Ho) Tutorial 2: Entity Search, Recommendation and Understanding (by Dr. Hao Ma) Workshop 1: Deep Learning Workshop 2: Machine Learning in China (MLChina'15)
10:30-11:00 Refreshment Break
11:00-12:30 Tutorial 1: A New Look at the System, Algorithm and Theory Foundations of Distributed Machine Learning (by Dr. Qirong Ho) Tutorial 2: Entity Search, Recommendation and Understanding (by Dr. Hao Ma) Workshop 1: Deep Learning Workshop 2: Machine Learning in China (MLChina'15)
12:30-14:30 Lunch Break (Self Arrangement)
14:30-16:00 Tutorial 3: Big Data Analytics: Optimization and Randomization (by Dr. Tianbao Yang) Tutorial 4: Causal Discovery and Inference: Traditional Approach and Recent Advances (by Dr. Kun Zhang and Dr. Jiji Zhang) Workshop 1: Deep Learning Workshop 2: Machine Learning in China (MLChina'15)
16:00-16:30 Refreshment Break
16:30-18:00 Tutorial 3: Big Data Analytics: Optimization and Randomization (by Dr. Tianbao Yang) Tutorial 4: Causal Discovery and Inference: Traditional Approach and Recent Advances (by Dr. Kun Zhang and Dr. Jiji Zhang) Workshop 1: Deep Learning Workshop 2: Machine Learning in China (MLChina'15)
18:30-20:30 Welcome Reception
Restaurant Name: Meraviglia Bar E Ristorante
Venue: S040 G/F Lakeside 2, No. 10 Science Park West Avenue, Hong Kong Science Park

Saturday, November 21, 2015: Main conference

Venue: Lecture Theater 1, Esther Lee Building, The Chinese University of Hong Kong

08:00 Registration
08:30-09:00 Opening Ceremony
09:00-10:00 Keynote Speech 1: Distributed Machine Learning on Big Data
Chaired by Prof. Irwin King, The Chinese University of Hong Kong
Speaker: Prof. Eric P. Xing, Carnegie Mellon University
10:00-10:30 Refreshment Break
Foyer outside Lecture Theatre 1
10:30-12:10 Session 1: Dimensionality reduction and feature selection
Chaired by Dr. Bob Durrant, University of Waikato
Geometry-Aware Principal Component Analysis for Symmetric Positive Definite Matrices
Inbal Horev, Florian Yger, Masashi Sugiyama
Non-asymptotic Analysis of Compressive Fisher Discriminants in terms of the Effective Dimension
Ata Kaban
Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities
Hiroaki Sasaki, Voot Tangkaratt, Masashi Sugiyama
Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias
Yohei Kondo, Shin-ichi Maeda, Kohei Hayashi
A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections
Ata Kaban
12:10-14:00 Lunch
Chung Chi College Staff Club
Poster Session
Foyer outside Lecture Theatre 1
14:00-14:40 Invited Talk 1: Recent Advances in Deep Learning: Learning Structured, Robust, and Multimodal Deep Models
Chaired by Dr. Tie-Yan Liu, Microsoft Research Asia
Speaker: Prof. Ruslan Salakhutdinov, University of Toronto
14:40-15:40 Session 2: Missing/Noisy labels
Chaired by Prof. Dit-Yan Yeung, Hong Kong University of Science and Technology
Consistency of structured output learning with missing labels
Kostiantyn Antoniuk, Vojtech Franc, Vaclav Hlavac
Maximum Margin Partial Label Learning
Fei Yu, Min-Ling Zhang
Robust Multivariate Regression with Grossly Corrupted Observations and Its Application to Personality Prediction
Xiaowei Zhang, Li Cheng, Tingshao Zhu
15:40-16:10 Refreshment Break
Foyer outside Lecture Theatre 1
16:10-16:50 Invited Talk 2: Making the Impossible Possible: Randomized Machine Learning Algorithms for Big Data
Chaired by Dr. Haiqin Yang, The Chinese University of Hong Kong
Speaker: Dr. Rong Jin, Alibaba
16:50-18:30 Session 3: Applications
Chaired by Prof. Masashi Sugiyama, University of Tokyo
Data-Guided Approach for Learning and Improving User Experience in Computer Networks
Yanan Bao, Xin Liu, Amit Pande
A Unified Framework for Jointly Learning Distributed Representations of Word and Attributes
Liqiang Niu, Xinyu Dai
Preference Relation-based Markov Random Fields
Shaowu Liu, Gang Li, Truyen Tran, Yuan Jiang
Detecting Accounting Frauds in Publicly Traded U.S. Firms: A Machine Learning Approach
Bin Li, Julia Yu, Jie Zhang, Bin Ke
Improving Sybil Detection via Graph Pruning and Regularization Techniques
Huanhuan Zhang, Jie Zhang, Carol Fung, Chang Xu
19:30-21:30 Banquet
Jasmine Room, Royal Park Hotel, Sha Tin
Coaches will be arranged for taking participants from Conference Venue to the Banquet

Sunday, November 22, 2015: Main conference

Venue: Lecture Theater 1, Esther Lee Building, The Chinese University of Hong Kong

08:00 Registration
08:30-09:30 Keynote Speech 2: Game Theoretic Understanding of Social Economic System Design
Chaired by Dr. Hang Li, Huawei Noah’s Ark Lab
Speaker: Prof. Xiaotie Deng, Shanghai Jiaotong University
9:30-10:10 Invited Talk 3: Bayesian Deep Learning for Integrated Intelligence: Bridging the Gap between Perception and Inference
Chaired by Prof. Geoffrey Holmes, Waikato University
Speaker: Prof. Dit-Yan Yeung, Hong Kong University of Science and Technology
10:10-10:40 Refreshment Break
Foyer outside Lecture Theatre 1
10:40-12:20 Session 4: Bayesian Methods
Chaired by Dr. Yang Yu, Nanjing Univeristy
Proximal Average Approximated Incremntal Gradient Method for Composite Penalty Regularized Empirical Risk Minimization
Yiu-ming Cheung, Jian Lou
Class-prior Estimation for Learning from Positive and Unlabeled Data
Marthinus Du Plessis, Gang Niu, Masashi Sugiyama
Streaming Variational Inference for Dirichlet Process Mixtures
Viet Huynh, Dinh Phung, Svetha Venkatesh
Expectation Propagation for Rectified Linear Poisson Regression
Young-Jun Ko, Matthias Seeger
Curriculum Learning of Bayesian Network Structures
Yanpeng Zhao, Yetian Chen, Kewei Tu, Jin Tian
12:20-14:00 Lunch
Chung Chi College Staff Club
Poster Session
Foyer outside Lecture Theatre 1
14:00-15:40 Session 5: Online/Reinforcement learning
Chaired by Prof. Xiaotie Deng, Shanghai Jiaotong University
Continuous Target Shift Adaptation in Supervised Learning
Duong Nguyen, Marthinus Du Plessis, Masashi Sugiyama
Surrogate regret bounds for generalized classification performance metrics
Wojciech Kotlowski, Krzysztof Dembczynski
Budgeted Bandit Problems with Continuous Random Costs
Wenkui Ding, Yingce Xia, Tao Qin
Regularized Policy Gradients: Direct Variance Reduction in Policy Gradient Estimation
Tingting Zhao, Gang Niu, Ning Xie, Jucheng Yang, Masashi Sugiyama
Statistical Unfolded Logic Learning
Wang-Zhou Dai, Zhi-Hua Zhou
15:40-16:10 Refreshment Break
Foyer outside Lecture Theatre 1
16:10-17:50 Session 6: Transfer/Multi-view/Deep learning
Chaired by Dr. Min-Ling Zhang, Southeast University
Integration of Single-view Graphs with Diffusion of Tensor Product Graphs for Multi-view Spectral Clustering
Le Shu, Longin Jan Latecki
Autoencoder Trees
Ozan Irsoy, Ethem Alpaydin
Similarity-based Contrastive Divergence Methods for Energy-based Deep Learning Models
Adepu Ravi Sankar, Vineeth N Balasubramanian
One-Pass Multi-View Learning
Yue Zhu, Wei Gao, Zhi-Hua Zhou
Largest Source-Subset Selection for Instance Transfer
Shuang Zhou, Gijs Schoenmakers, Evguen Smirnov, Siqi Chen, Kurt Driessens, Ralf Peeters
17:50-18:10 Closing Ceremony