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Regression

5,004 papers

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Papers

DECOrrelated feature space partitioning for distributed sparse regression NIPS 2016
A Bandit Framework for Strategic Regression NIPS 2016
Joint quantile regression in vector-valued RKHSs NIPS 2016
Scaled Least Squares Estimator for GLMs in Large-Scale Problems NIPS 2016
High resolution neural connectivity from incomplete tracing data using nonnegative spline regression NIPS 2016
Scalable Structure Discovery in Regression using Gaussian Processes AUTOML 2016
Multitask Principal Component Analysis ACML 2016
Learning Sparse Additive Models with Interactions in High Dimensions AISTATS 2016
Maximum Likelihood for Variance Estimation in High-Dimensional Linear Models AISTATS 2016
Precision Matrix Estimation in High Dimensional Gaussian Graphical Models with Faster Rates AISTATS 2016
Deep Kernel Learning AISTATS 2016
A Lasso-based Sparse Knowledge Gradient Policy for Sequential Optimal Learning AISTATS 2016
Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models AISTATS 2016
Learning Relationships between Data Obtained Independently AISTATS 2016
Probabilistic Approximate Least-Squares AISTATS 2016
Sequential Inference for Deep Gaussian Process AISTATS 2016
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo AISTATS 2016
Distributed Multi-Task Learning AISTATS 2016
Ordered Weighted L1 Regularized Regression with Strongly Correlated Covariates: Theoretical Aspects AISTATS 2016
Provable Tensor Methods for Learning Mixtures of Generalized Linear Models AISTATS 2016
Robust Covariate Shift Regression AISTATS 2016
Back to the Future: Radial Basis Function Networks Revisited AISTATS 2016
Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions AISTATS 2016
NYTRO: When Subsampling Meets Early Stopping AISTATS 2016
Spectral M-estimation with Applications to Hidden Markov Models AISTATS 2016