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Poster
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Tue 10:45
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Causal Regularization
Dominik Janzing
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Social
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Tue 19:00
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Learning Theory (Definitions, Theorems, Proofs, etc.)
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Poster
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Thu 17:00
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Distinguishing Distributions When Samples Are Strategically Transformed
Hanrui Zhang · Yu Cheng · Vincent Conitzer
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Poster
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Tue 17:30
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Optimal Best Markovian Arm Identification with Fixed Confidence
Vrettos Moulos
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Poster
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Tue 17:30
|
Adaptive Gradient-Based Meta-Learning Methods
Misha Khodak · Maria-Florina Balcan · Ameet Talwalkar
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|
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Poster
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Tue 10:45
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Capacity Bounded Differential Privacy
Kamalika Chaudhuri · Jacob Imola · Ashwin Machanavajjhala
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|
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Workshop
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Sat 8:15
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Surya Ganguli - An analytic theory of generalization dynamics and transfer learning in deep linear networks
Surya Ganguli
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Poster
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Wed 17:00
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Generalization Bounds for Neural Networks via Approximate Description Length
Amit Daniely · Elad Granot
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Poster
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Wed 17:00
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Computational Separations between Sampling and Optimization
Kunal Talwar
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Poster
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Tue 17:30
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Connections Between Mirror Descent, Thompson Sampling and the Information Ratio
Julian Zimmert · Tor Lattimore
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Poster
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Tue 17:30
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On the Correctness and Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru · Jean Honorio
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Poster
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Tue 10:45
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Exact inference in structured prediction
Kevin Bello · Jean Honorio
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