generalized linear model

Tree-projected gradient descent for estimating gradient-sparse parameters on graphs COLT 2020 Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance COLT 2019 Binarsity: a penalization for one-hot encoded features in linear supervised learning JMLR 2019 Feature subset selection for the multinomial logit model via mixed-integer optimization AISTATS 2019 Generalized Linear Rule Models ICML 2019 LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations ICML 2019 Multi-Objective Generalized Linear Bandits IJCAI 2019 Nonuniformity of P-values Can Occur Early in Diverging Dimensions JMLR 2019 Scalable Approximations for Generalized Linear Problems JMLR 2019 Sketched Iterative Algorithms for Structured Generalized Linear Models IJCAI 2019 A Distributed Second-Order Algorithm You Can Trust ICML 2018 Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models COLT 2018 Scaling the Poisson GLM to massive neural datasets through polynomial approximations NeurIPS 2018 Snap ML: A Hierarchical Framework for Machine Learning NeurIPS 2018 tick: a Python Library for Statistical Learning, with an emphasis on Hawkes Processes and Time-Dependent Models JMLR 2018 Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems NeurIPS 2017 Gap Safe Screening Rules for Sparsity Enforcing Penalties JMLR 2017 Generalized Linear Model Regression under Distance-to-set Penalties NeurIPS 2017 PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference NeurIPS 2017 Provably Optimal Algorithms for Generalized Linear Contextual Bandits ICML 2017 Bayesian latent structure discovery from multi-neuron recordings NeurIPS 2016 Exponential Family Embeddings NeurIPS 2016 Newton-Stein Method: An Optimization Method for GLMs via Stein's Lemma JMLR 2016 Primal-Dual Rates and Certificates ICML 2016 Provable Tensor Methods for Learning Mixtures of Generalized Linear Models AISTATS 2016