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Poster
Tue 8:00 Nonparametric Score Estimators
Yuhao Zhou · Jiaxin Shi · Jun Zhu
Poster
Tue 9:00 Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features
Liang Ding · Rui Tuo · Shahin Shahrampour
Poster
Tue 9:00 Disentangling Trainability and Generalization in Deep Neural Networks
Lechao Xiao · Jeffrey Pennington · Samuel Schoenholz
Poster
Tue 10:00 Harmonic Decompositions of Convolutional Networks
Meyer Scetbon · Zaid Harchaoui
Poster
Tue 10:00 Structured Prediction with Partial Labelling through the Infimum Loss
Vivien Cabannnes · Alessandro Rudi · Francis Bach
Poster
Tue 11:00 Learning Deep Kernels for Non-Parametric Two-Sample Tests
Feng Liu · Wenkai Xu · Jie Lu · Guangquan Zhang · Arthur Gretton · D.J. Sutherland
Poster
Tue 11:00 Kernel Methods for Cooperative Multi-Agent Contextual Bandits
Abhimanyu Dubey · Alex `Sandy' Pentland
Poster
Tue 13:00 Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses
Pierre Laforgue · Alex Lambert · Luc Brogat-Motte · Florence d'Alche-Buc
Poster
Tue 14:00 Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling
David Woodruff · Amir Zandieh
Poster
Tue 18:00 Learning to Learn Kernels with Variational Random Features
Xiantong Zhen · Haoliang Sun · Yingjun Du · Jun Xu · Yilong Yin · Ling Shao · Cees Snoek
Poster
Wed 5:00 Dynamics of Deep Neural Networks and Neural Tangent Hierarchy
Jiaoyang Huang · Horng-Tzer Yau
Poster
Wed 8:00 Randomly Projected Additive Gaussian Processes for Regression
Ian Delbridge · David S Bindel · Andrew Wilson