Poster

Thu 6:00

Learning the Valuations of a $k$-demand Agent
Hanrui Zhang · Vincent Conitzer

Poster

Thu 7:00

Generalization via Derandomization
Jeffrey Negrea · Gintare Karolina Dziugaite · Daniel Roy

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

Wed 11:00

The Implicit and Explicit Regularization Effects of Dropout
Colin Wei · Sham Kakade · Tengyu Ma

Poster

Thu 6:00

Strategic Classification is Causal Modeling in Disguise
John Miller · Smitha Milli · Moritz Hardt

Poster

Tue 9:00

Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization
Sicheng Zhu · Xiao Zhang · David Evans