Papers
A Geometric Perspective on the Transferability of Adversarial Directions
Zachary Charles, Harrison Rosenberg, Dimitris Papailiopoulos
Learning One-hidden-layer Neural Networks under General Input Distributions
Weihao Gao, Ashok V. Makkuva, Sewoong Oh et al.
Stochastic Negative Mining for Learning with Large Output Spaces
Sashank J. Reddi, Satyen Kale, Felix Yu et al.
Designing Optimal Binary Rating Systems
Nikhil Garg, Ramesh Johari
Sharp Analysis of Learning with Discrete Losses
Alex Nowak, Francis Bach, Alessandro Rudi
Exponential Weights on the Hypercube in Polynomial Time
Sudeep Raja Putta, Abhishek Shetty
Probabilistic Forecasting with Spline Quantile Function RNNs
Jan Gasthaus, Konstantinos Benidis, Yuyang Wang et al.
Sequential Patient Recruitment and Allocation for Adaptive Clinical Trials
Onur Atan, William R. Zame, Mihaela Schaar
Unsupervised Alignment of Embeddings with Wasserstein Procrustes
Edouard Grave, Armand Joulin, Quentin Berthet
Towards Optimal Transport with Global Invariances
David Alvarez-Melis, Stefanie Jegelka, Tommi S. Jaakkola
The Gaussian Process Autoregressive Regression Model (GPAR)
James Requeima, William Tebbutt, Wessel Bruinsma et al.
MaxHedge: Maximizing a Maximum Online
Stephen Pasteris, Fabio Vitale, Kevin Chan et al.
Generalizing the theory of cooperative inference
Pei Wang, Pushpi Paranamana, Patrick Shafto
Large-Margin Classification in Hyperbolic Space
Hyunghoon Cho, Benjamin DeMeo, Jian Peng et al.
Data-dependent compression of random features for large-scale kernel approximation
Raj Agrawal, Trevor Campbell, Jonathan Huggins et al.
Deep learning with differential Gaussian process flows
Pashupati Hegde, Markus Heinonen, Harri Lähdesmäki et al.
Negative Momentum for Improved Game Dynamics
Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki et al.
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
Shikhar Vashishth, Prateek Yadav, Manik Bhandari et al.
Active multiple matrix completion with adaptive confidence sets
Andrea Locatelli, Alexandra Carpentier, Michal Valko
Learning Tree Structures from Noisy Data
Konstantinos E. Nikolakakis, Dionysios S. Kalogerias, Anand D. Sarwate
Causal Discovery in the Presence of Missing Data
Ruibo Tu, Cheng Zhang, Paul Ackermann et al.
Lifted Weight Learning of Markov Logic Networks Revisited
Ondrej Kuzelka, Vyacheslav Kungurtsev
Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution
Topi Paananen, Juho Piironen, Michael Riis Andersen et al.
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data
Victor Veitch, Morgane Austern, Wenda Zhou et al.
Truncated Back-propagation for Bilevel Optimization
Amirreza Shaban, Ching-An Cheng, Nathan Hatch et al.