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- [ 64932 ] Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning
- [ 64933 ] Estimating graphical models for count data with applications to single-cell gene network
- [ 64934 ] Concentration of Data Encoding in Parameterized Quantum Circuits
- [ 64935 ] On Learning Fairness and Accuracy on Multiple Subgroups
- [ 64936 ] Panchromatic and Multispectral Image Fusion via Alternating Reverse Filtering Network
- [ 64938 ] Doubly Robust Counterfactual Classification
- [ 64939 ] Trading off Image Quality for Robustness is not Necessary with Regularized Deterministic Autoencoders
Q&A on RocketChat immediately following Lightning Talks
Author Information
Feiyi Xiao (Peking University)
Amrutha Saseendran (Bosch Center for Artificial Intelligence)
Kwangho Kim (Harvard University)
Keyu Yan (University of Science and Technology of China)
Changjian Shui (McGill University)
Guangxi Li (University of Technology Sydney)
Shikun Li (Institute of Information Engineering,Chinese Academy of Sciences)
Edward Kennedy (Carnegie Mellon University)
Man Zhou (Hefei Institutes of Physical Science, Chinese Academy of Sciences)
Gezheng Xu (University of Western Ontario)
Ruilin Ye (Peking University)
Xiaobo Xia (The University of Sydney)
Junjie Tang (Peking university)
Kathrin Skubch (Bosch Center for Artificial Intelligence)
Stefan Falkner (University of Freiburg)
Hansong Zhang (University of the Chinese Academy of Sciences)
Jose Zubizarreta (Harvard University)
Huaying Fang (Capital Normal University)
Xuanqiang Zhao (The University of Hong Kong)
Jie Huang (University of Science and Technology of China)
Qi CHEN (Laval University)
Yibing Zhan (JD Explore Academy)
Jiaqi Li (University of Western Ontario)
Xin Wang (Baidu)
Ruibin Xi (Peking University)
Feng Zhao (University of Science and Technology of China)
Margret Keuper (University of Mannheim)
Charles Ling (University of Western Ontario)
Shiming Ge (Institute of Information Engineering, Chinese Academy of Sciences)
Chengjun Xie (Hefei Institutes of Physical Science, Chinese Academy of Sciences)
Tongliang Liu (The University of Sydney)
Tal Arbel (McGill University)
Chongyi Li (City University of Hong Kong)
Danfeng Hong (Aerospace Information Research Institute, Chinese Academy of Sciences)
Boyu Wang (University of Western Ontario)
Christian Gagné (Université Laval)
Christian Gagné is a professor at the Electrical Engineering and Computer Engineering Department of Université Laval since 2008. He is the director of the Institute Intelligence and Data (IID) of l’Université Laval. He holds a Canada-CIFAR Artificial Intelligence Chair and is an associate member to Mila. He is also a member of the Computer Vision and Systems Laboratory (CVSL), a component of the Robotics, Vision and Machine Intelligence Research Centre (CeRVIM), and the Big Data Research Centre (BDRC) of Université Laval. He is also participating to the REPARTI and UNIQUE strategic clusters of the FRQNT, the VITAM FRQS center and the International Observatory on the Societal Impacts of AI (OBVIA). He completed a PhD in Electrical Engineering (Université Laval) in 2005 and then had a postdoctoral stay jointly at INRIA Saclay (France) and the University of Lausanne (Switzerland) in 2005-2006. He worked as research associate in the industry between 2006 and 2008. He is a member of executive board the ACM Special Interest Group on Evolutionary Computation (SIGEVO) since 2017. His research interests are on the development of methods for machine learning and stochastic optimization. In particular, he is interested by deep neural networks, representation learning and transfer, meta-learning and multitask learning. He is also interested by optimization approaches based on probabilistic models and evolutionary algorithms for black-box optimization and automatic programming, among others. A significant share of his research work is on the practical use of these techniques in domains such as computer vision, microscopy, health, energy and transportation.
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