conftrace_

generalized linear model

138 papers

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Also known as

GLM

Co-occurring keywords

bayesian inference (1907) regret bound (1926) maximum likelihood estimation (233) logistic regression (386) high-dimensional statistics (145) maximum likelihood (255) approximate message passing (39) online learning (1777) variable selection (146) differential privacy (1016)

Papers

Safe-Bayesian Generalized Linear Regression AISTATS 2020
Minimax Bounds for Generalized Linear Models NIPS 2020
Learning nonlinear dynamical systems from a single trajectory L4DC 2020
Generalization Error of Generalized Linear Models in High Dimensions ICML 2020
A Regularization-Based Adaptive Test for High-Dimensional GLMs JMLR 2020
Distributionally Robust Parametric Maximum Likelihood Estimation NIPS 2020
Dual Extrapolation for Sparse GLMs JMLR 2020
Improved Optimistic Algorithms for Logistic Bandits ICML 2020
No-regret Exploration in Contextual Reinforcement Learning UAI 2020
A new inference approach for training shallow and deep generalized linear models of noisy interacting neurons NIPS 2020
Scalable Approximations for Generalized Linear Problems JMLR 2019
Binarsity: a penalization for one-hot encoded features in linear supervised learning JMLR 2019
Nonuniformity of P-values Can Occur Early in Diverging Dimensions JMLR 2019
Sketched Iterative Algorithms for Structured Generalized Linear Models IJCAI 2019
Feature subset selection for the multinomial logit model via mixed-integer optimization AISTATS 2019
Multi-Objective Generalized Linear Bandits IJCAI 2019
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations ICML 2019
Generalized Linear Rule Models ICML 2019
Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance COLT 2019
Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models COLT 2018
Scaling the Poisson GLM to massive neural datasets through polynomial approximations NIPS 2018
A Distributed Second-Order Algorithm You Can Trust ICML 2018
Snap ML: A Hierarchical Framework for Machine Learning NIPS 2018
tick: a Python Library for Statistical Learning, with an emphasis on Hawkes Processes and Time-Dependent Models JMLR 2018
Gap Safe Screening Rules for Sparsity Enforcing Penalties JMLR 2017