Papers
Generative causal explanations of black-box classifiers
Matthew O'Shaughnessy, Gregory Canal, Marissa Connor et al.
Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry
Yossi Arjevani, Michael Field
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits
Pierre Perrault, Etienne Boursier, Michal Valko et al.
Agnostic Learning of a Single Neuron with Gradient Descent
Spencer Frei, Yuan Cao, Quanquan Gu
Parabolic Approximation Line Search for DNNs
Maximus Mutschler, Andreas Zell
Adam with Bandit Sampling for Deep Learning
Rui Liu, Tianyi Wu, Barzan Mozafari
Learning to Orient Surfaces by Self-supervised Spherical CNNs
Riccardo Spezialetti, Federico Stella, Marlon Marcon et al.
Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm
Tianyi Lin, Nhat Ho, Xi Chen et al.
An analytic theory of shallow networks dynamics for hinge loss classification
Franco Pellegrini, Giulio Biroli
Robust Density Estimation under Besov IPM Losses
Ananya Uppal, Shashank Singh, Barnabas Poczos
Federated Accelerated Stochastic Gradient Descent
Honglin Yuan, Tengyu Ma
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming
Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin et al.
Robust Quantization: One Model to Rule Them All
moran shkolnik, Brian Chmiel, Ron Banner et al.
Counterfactual Vision-and-Language Navigation: Unravelling the Unseen
Amin Parvaneh, Ehsan Abbasnejad, Damien Teney et al.
Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction
Mariya Toneva, Otilia Stretcu, Barnabas Poczos et al.
Dirichlet Graph Variational Autoencoder
Jia Li, Jianwei Yu, Jiajin Li et al.
Second Order PAC-Bayesian Bounds for the Weighted Majority Vote
Andres Masegosa, Stephan Lorenzen, Christian Igel et al.
Sparse Graphical Memory for Robust Planning
Scott Emmons, Ajay N. Jain, Misha Laskin et al.
Multiscale Deep Equilibrium Models
Shaojie Bai, Vladlen Koltun, J. Zico Kolter
Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning
Chandrashekar Lakshminarayanan, Amit Vikram Singh
A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling
Xiaotie Deng, Ron Lavi, Tao Lin et al.
Noise-Contrastive Estimation for Multivariate Point Processes
Hongyuan Mei, Tom Wan, Jason Eisner
Robust Optimization for Fairness with Noisy Protected Groups
Serena Wang, Wenshuo Guo, Harikrishna Narasimhan et al.
Learning Physical Constraints with Neural Projections
Shuqi Yang, Xingzhe He, Bo Zhu
Certifying Confidence via Randomized Smoothing
Aounon Kumar, Alexander Levine, Soheil Feizi et al.