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Poster
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Wed 18:30
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Repeated Inverse Reinforcement Learning
Kareem Amin · Nan Jiang · Satinder Singh
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Poster
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Mon 18:30
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Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions
Aryeh Kontorovich · Sivan Sabato · Roi Weiss
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Poster
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Mon 18:30
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From which world is your graph
Cheng Li · Felix MF Wong · Zhenming Liu · Varun Kanade
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Poster
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Wed 18:30
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Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues
Noga Alon · Moshe Babaioff · Yannai A. Gonczarowski · Yishay Mansour · Shay Moran · Amir Yehudayoff
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Poster
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Wed 18:30
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Optimal Sample Complexity of M-wise Data for Top-K Ranking
Minje Jang · Sunghyun Kim · Changho Suh · Sewoong Oh
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Poster
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Tue 18:30
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Best Response Regression
Omer Ben-Porat · Moshe Tennenholtz
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Poster
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Tue 18:30
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Linear regression without correspondence
Daniel Hsu · Kevin Shi · Xiaorui Sun
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Poster
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Wed 18:30
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Online Convex Optimization with Stochastic Constraints
Hao Yu · Michael Neely · Xiaohan Wei
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Poster
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Wed 18:30
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Learning Unknown Markov Decision Processes: A Thompson Sampling Approach
Yi Ouyang · Mukul Gagrani · Ashutosh Nayyar · Rahul Jain
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Workshop
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Sat 8:30
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François Laviolette - A Tutorial on PAC-Bayesian Theory
Francois Laviolette
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Workshop
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Fri 9:00
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On Structured Prediction Theory with Calibrated Convex Surrogate Losses.
Simon Lacoste-Julien
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Workshop
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Fri 10:00
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Learning theory and algorithms for shapelets and other local features. Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai and Akiko Takeda.
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