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Poster
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Tue 10:45
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Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks
Yuan Cao · Quanquan Gu
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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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Poster
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Wed 10:45
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An Embedding Framework for Consistent Polyhedral Surrogates
Jessica Finocchiaro · Rafael Frongillo · Bo Waggoner
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Poster
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Tue 17:30
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Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle
Simon Du · Yuping Luo · Ruosong Wang · Hanrui Zhang
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Poster
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Thu 17:00
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Theoretical Analysis of Adversarial Learning: A Minimax Approach
Zhuozhuo Tu · Jingwei Zhang · Dacheng Tao
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Poster
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Thu 17:00
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Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates
Jeffrey Negrea · Mahdi Haghifam · Gintare Karolina Dziugaite · Ashish Khisti · Daniel Roy
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Poster
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Thu 10:45
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Learning Stable Deep Dynamics Models
J. Zico Kolter · Gaurav Manek
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Poster
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Wed 17:00
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On Making Stochastic Classifiers Deterministic
Andrew Cotter · Maya Gupta · Harikrishna Narasimhan
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Poster
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Thu 10:45
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Paradoxes in Fair Machine Learning
Paul Gölz · Anson Kahng · Ariel Procaccia
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Poster
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Wed 17:00
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Graph-based Discriminators: Sample Complexity and Expressiveness
Roi Livni · Yishay Mansour
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Poster
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Tue 17:30
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Toward a Characterization of Loss Functions for Distribution Learning
Nika Haghtalab · Cameron Musco · Bo Waggoner
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Poster
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Thu 17:00
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Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks
Spencer Frei · Yuan Cao · Quanquan Gu
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