Mason, Blake

13 publications

UAI 2025 Metric Learning in an RKHS Gokcan Tatli, Yi Chen, Blake Mason, Robert D Nowak, Ramya Korlakai Vinayak

AISTATS 2023 A Blessing of Dimensionality in Membership Inference Through Regularization Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk

NeurIPS 2023 Experimental Designs for Heteroskedastic Variance Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain

AISTATS 2022 Nearly Optimal Algorithms for Level Set Estimation Blake Mason, Lalit Jain, Subhojyoti Mukherjee, Romain Camilleri, Kevin Jamieson, Robert Nowak

AAAI 2022 An Experimental Design Approach for Regret Minimization in Logistic Bandits Blake Mason, Kwang-Sung Jun, Lalit Jain

NeurIPS 2022 One for All: Simultaneous Metric and Preference Learning over Multiple Users Gregory Canal, Blake Mason, Ramya Korlakai Vinayak, Robert Nowak

NeurIPS 2022 Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference Jasper Tan, Blake Mason, Hamid Javadi, Richard Baraniuk

ICML 2021 Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits Kwang-Sung Jun, Lalit Jain, Blake Mason, Houssam Nassif

UAI 2021 Nearest Neighbor Search Under Uncertainty Blake Mason, Ardhendu Tripathy, Robert Nowak

NeurIPS 2021 Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers Julian Katz-Samuels, Blake Mason, Kevin G. Jamieson, Rob Nowak

NeurIPS 2020 Finding All $\epsilon$-Good Arms in Stochastic Bandits Blake Mason, Lalit Jain, Ardhendu Tripathy, Robert Nowak

NeurIPS 2019 Learning Nearest Neighbor Graphs from Noisy Distance Samples Blake Mason, Ardhendu Tripathy, Robert Nowak

NeurIPS 2017 Learning Low-Dimensional Metrics Blake Mason, Lalit Jain, Robert Nowak