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The 2021 schedule is still incomplete
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Oral
Wed Jul 21 11:00 PM -- 11:20 PM (KST)
PAC-Learning for Strategic Classification
In Learning Theory 6
Ravi Sundaram · Anil Vullikanti · Haifeng Xu · Fan Yao
[ Paper ]
Spotlight
Wed Jul 21 11:20 PM -- 11:25 PM (KST)
Learning from Biased Data: A Semi-Parametric Approach
In Learning Theory 6
Patrice Bertail · Stephan Clémençon · Yannick Guyonvarch · Nathan NOIRY
[ Paper ]
Spotlight
Wed Jul 21 11:25 PM -- 11:30 PM (KST)
Learning in Nonzero-Sum Stochastic Games with Potentials
In Learning Theory 6
David Mguni · Yutong Wu · Yali Du · Yaodong Yang · Ziyi Wang · Minne Li · Ying Wen · Joel Jennings · Jun Wang
[ Paper ]
Spotlight
Wed Jul 21 11:30 PM -- 11:35 PM (KST)
Guarantees for Tuning the Step Size using a Learning-to-Learn Approach
In Learning Theory 6
Xiang Wang · Shuai Yuan · Chenwei Wu · Rong Ge
[ Paper ]
Spotlight
Wed Jul 21 11:35 PM -- 11:40 PM (KST)
Large-Scale Multi-Agent Deep FBSDEs
In Learning Theory 6
Tianrong Chen · Ziyi Wang · Ioannis Exarchos · Evangelos Theodorou
[ Paper ]
Spotlight
Wed Jul 21 11:40 PM -- 11:45 PM (KST)
Multi-group Agnostic PAC Learnability
In Learning Theory 6
Guy Rothblum · Gal Yona
[ Paper ]
Spotlight
Wed Jul 21 11:45 PM -- 11:50 PM (KST)
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning
In Learning Theory 6
Avrim Blum · Nika Haghtalab · Richard Lanas Phillips · Han Shao
[ Paper ]
Q&A
Wed Jul 21 11:50 PM -- 11:55 PM (KST)
Q&A
In Learning Theory 6