generalized linear model

Evading the Curse of Dimensionality in Unconstrained Private GLMs AISTATS 2021 Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions AISTATS 2021 Generalized Linear Bandits with Local Differential Privacy NeurIPS 2021 Hessian Eigenspectra of More Realistic Nonlinear Models NeurIPS 2021 Improving predictions of Bayesian neural nets via local linearization AISTATS 2021 Jump-Starting Item Parameters for Adaptive Language Tests EMNLP 2021 Learning the Truth From Only One Side of the Story AISTATS 2021 Leveraging Non-uniformity in First-order Non-convex Optimization ICML 2021 Online stochastic gradient descent on non-convex losses from high-dimensional inference JMLR 2021 Reconsidering Annotator Disagreement about Racist Language: Noise or Signal? NAACL 2021 Robust Regression Revisited: Acceleration and Improved Estimation Rates NeurIPS 2021 Safe Policy Optimization with Local Generalized Linear Function Approximations NeurIPS 2021 Stochastic Online Optimization using Kalman Recursion JMLR 2021 Taming heavy-tailed features by shrinkage AISTATS 2021 A new inference approach for training shallow and deep generalized linear models of noisy interacting neurons NeurIPS 2020 A Regularization-Based Adaptive Test for High-Dimensional GLMs JMLR 2020 Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Evolvability NeurIPS 2020 Distributionally Robust Parametric Maximum Likelihood Estimation NeurIPS 2020 Dual Extrapolation for Sparse GLMs JMLR 2020 Generalization Error of Generalized Linear Models in High Dimensions ICML 2020 Improved Optimistic Algorithms for Logistic Bandits ICML 2020 Learning nonlinear dynamical systems from a single trajectory L4DC 2020 Minimax Bounds for Generalized Linear Models NeurIPS 2020 No-regret Exploration in Contextual Reinforcement Learning UAI 2020 Safe-Bayesian Generalized Linear Regression AISTATS 2020