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Regression

5,004 papers

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Papers

Accurate Uncertainties for Deep Learning Using Calibrated Regression ICML 2018
An Estimation and Analysis Framework for the Rasch Model ICML 2018
The Well-Tempered Lasso ICML 2018
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods ICML 2018
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces ICML 2018
Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap ICML 2018
Constraining the Dynamics of Deep Probabilistic Models ICML 2018
Celer: a Fast Solver for the Lasso with Dual Extrapolation ICML 2018
Ranking Distributions based on Noisy Sorting ICML 2018
WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models ICML 2018
Transformation Autoregressive Networks ICML 2018
Learning Localized Spatio-Temporal Models From Streaming Data ICML 2018
Autoregressive Quantile Networks for Generative Modeling ICML 2018
Efficient First-Order Algorithms for Adaptive Signal Denoising ICML 2018
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach ICML 2018
Selecting Representative Examples for Program Synthesis ICML 2018
Learning Equations for Extrapolation and Control ICML 2018
Adversarial Regression with Multiple Learners ICML 2018
Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates ICML 2018
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions ICML 2018
SQL-Rank: A Listwise Approach to Collaborative Ranking ICML 2018
Nonoverlap-Promoting Variable Selection ICML 2018
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information ICML 2018
Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data ICML 2018
Variable Selection via Penalized Neural Network: a Drop-Out-One Loss Approach ICML 2018