| Convergence Guarantees for Adaptive Bayesian Quadrature Methods | Motonobu Kanagawa · Philipp Hennig |
| Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses | Ulysse Marteau-Ferey · Francis Bach · Alessandro Rudi |
| Kernel Instrumental Variable Regression | Rahul Singh · Maneesh Sahani · Arthur Gretton |
| Kernel Stein Tests for Multiple Model Comparison | Jen Ning Lim · Makoto Yamada · Bernhard Schölkopf · Wittawat Jitkrittum |
| On Exact Computation with an Infinitely Wide Neural Net | Sanjeev Arora · Simon Du · Wei Hu · Zhiyuan Li · Russ Salakhutdinov · Ruosong Wang |
| Solving Interpretable Kernel Dimensionality Reduction | Chieh Wu · Jared Miller · Yale Chang · Mario Sznaier · Jennifer Dy |
| Comparing distributions: \ell_1 geometry improves kernel two-sample testing | meyer scetbon · Gael Varoquaux |
| Distributionally Robust Optimization and Generalization in Kernel Methods | Matthew Staib · Stefanie Jegelka |
| Learning metrics for persistence-based summaries and applications for graph classification | Qi Zhao · Yusu Wang |
| Minimum Stein Discrepancy Estimators | Alessandro Barp · Francois-Xavier Briol · Andrew Duncan · Mark Girolami · Lester Mackey |
| Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels | Michela Meister · Tamas Sarlos · David Woodruff |
| Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test | Lizhong Ding · Mengyang Yu · Li Liu · Fan Zhu · Yong Liu · Yu Li · Ling Shao |
| Wasserstein Weisfeiler-Lehman Graph Kernels | Matteo Togninalli · Elisabetta Ghisu · Felipe Llinares-López · Bastian Rieck · Karsten Borgwardt |