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Regression

5,004 papers

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Papers

Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks ACML 2017
Data sparse nonparametric regression with $ε$-insensitive losses ACML 2017
Magnitude-Preserving Ranking for Structured Outputs ACML 2017
Minimax Density Estimation for Growing Dimension AISTATS 2017
Generalized Pseudolikelihood Methods for Inverse Covariance Estimation AISTATS 2017
Localized Lasso for High-Dimensional Regression AISTATS 2017
ConvNets with Smooth Adaptive Activation Functions for Regression AISTATS 2017
Minimax Approach to Variable Fidelity Data Interpolation AISTATS 2017
Rank Aggregation and Prediction with Item Features AISTATS 2017
Regression Uncertainty on the Grassmannian AISTATS 2017
Attributing Hacks AISTATS 2017
Minimax-optimal semi-supervised regression on unknown manifolds AISTATS 2017
Frequency Domain Predictive Modelling with Aggregated Data AISTATS 2017
Identifying Groups of Strongly Correlated Variables through Smoothed Ordered Weighted $L_1$-norms AISTATS 2017
A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models AISTATS 2017
Compressed Least Squares Regression revisited AISTATS 2017
Prediction Performance After Learning in Gaussian Process Regression AISTATS 2017
Information Projection and Approximate Inference for Structured Sparse Variables AISTATS 2017
Value-Aware Loss Function for Model-based Reinforcement Learning AISTATS 2017
Rates of estimation for determinantal point processes COLT 2017
Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$ COLT 2017
Matrix Completion from $O(n)$ Samples in Linear Time COLT 2017
High Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transtition COLT 2017
Modeling Context Words as Regions: An Ordinal Regression Approach to Word Embedding CONLL 2017
Counting Everyday Objects in Everyday Scenes CVPR 2017