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Talk
Tue 23:42 Nyström Method with Kernel K-means++ Samples as Landmarks
Dino Oglic · Thomas Gaertner
Poster
Wed 1:30 Nyström Method with Kernel K-means++ Samples as Landmarks
Dino Oglic · Thomas Gaertner
Poster
Tue 18:30 Scalable Learning in Reproducing Kernel Krein Spaces
Dino Oglic · Thomas Gaertner
Poster
Tue 18:30 Towards a Unified Analysis of Random Fourier Features
Zhu Li · Jean-Francois Ton · Dino Oglic · Dino Sejdinovic
Poster
Tue 18:30 Bayesian Deconditional Kernel Mean Embeddings
Kelvin Hsu · Fabio Ramos
Poster
Tue 18:30 Learning deep kernels for exponential family densities
Li Kevin Wenliang · D.J. Sutherland · Heiko Strathmann · Arthur Gretton
Poster
Tue 18:30 Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension
Jisu Kim · Jaehyeok Shin · Alessandro Rinaldo · Larry Wasserman
Poster
Tue 18:30 Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates
George Chen
Poster
Tue 18:30 A Persistent Weisfeiler--Lehman Procedure for Graph Classification
Bastian Rieck · Christian Bock · Karsten Borgwardt
Poster
Tue 18:30 Particle Flow Bayes' Rule
Xinshi Chen · Hanjun Dai · Le Song
Poster
Tue 18:30 Large-Scale Sparse Kernel Canonical Correlation Analysis
Viivi Uurtio · Sahely Bhadra · Juho Rousu
Poster
Tue 18:30 Rehashing Kernel Evaluation in High Dimensions
Paris Siminelakis · Kexin Rong · Peter Bailis · Moses Charikar · Philip Levis