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Oral
Thu Dec 12 03:50 PM -- 04:05 PM (PST) @ West Ballroom A + B
Blind Super-Resolution Kernel Estimation using an Internal-GAN
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Thu Dec 12 04:05 PM -- 04:10 PM (PST) @ West Ballroom A + B
Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance
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Thu Dec 12 04:10 PM -- 04:15 PM (PST) @ West Ballroom A + B
Theoretical Analysis of Adversarial Learning: A Minimax Approach
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Thu Dec 12 04:15 PM -- 04:20 PM (PST) @ West Ballroom A + B
Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem
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Thu Dec 12 04:20 PM -- 04:25 PM (PST) @ West Ballroom A + B
Differentiable Ranking and Sorting using Optimal Transport
Oral
Thu Dec 12 04:25 PM -- 04:40 PM (PST) @ West Ballroom A + B
Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses
Spotlight
Thu Dec 12 04:40 PM -- 04:45 PM (PST) @ West Ballroom A + B
KerGM: Kernelized Graph Matching
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Thu Dec 12 04:45 PM -- 04:50 PM (PST) @ West Ballroom A + B
Wasserstein Weisfeiler-Lehman Graph Kernels
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Thu Dec 12 04:50 PM -- 04:55 PM (PST) @ West Ballroom A + B
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel
Spotlight
Thu Dec 12 04:55 PM -- 05:00 PM (PST) @ West Ballroom A + B
Comparing distributions: $\ell_1$ geometry improves kernel two-sample testing