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Poster
Thu 7:00 Generalization via Derandomization
Jeffrey Negrea · Gintare Karolina Dziugaite · Daniel Roy
Poster
Thu 6:00 Learning the Valuations of a $k$-demand Agent
Hanrui Zhang · Vincent Conitzer
Workshop
Fri 6:05 Invited Talk: Christoph H. Lampert "Learning Theory for Continual and Meta-Learning"
Christoph H. Lampert
Poster
Thu 9:00 A Distributional Framework For Data Valuation
Amirata Ghorbani · Michael Kim · James Zou
Poster
Thu 7:00 Goodness-of-Fit Tests for Inhomogeneous Random Graphs
Soham Dan · Bhaswar B. Bhattacharya
Poster
Wed 5:00 Learning Opinions in Social Networks
Vincent Conitzer · Debmalya Panigrahi · Hanrui Zhang
Poster
Tue 11:00 Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
Zitong Yang · Yaodong Yu · Chong You · Jacob Steinhardt · Yi Ma
Poster
Wed 8:00 Black-box Certification and Learning under Adversarial Perturbations
Hassan Ashtiani · Vinayak Pathak · Ruth Urner
Poster
Thu 6:00 Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification
Chen Dan · Yuting Wei · Pradeep Ravikumar
Poster
Thu 6:00 Strategic Classification is Causal Modeling in Disguise
John Miller · Smitha Milli · Moritz Hardt
Poster
Wed 11:00 The Implicit and Explicit Regularization Effects of Dropout
Colin Wei · Sham Kakade · Tengyu Ma
Poster
Tue 9:00 Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization
Sicheng Zhu · Xiao Zhang · David Evans