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Regression

4964 directly classified papers

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Papers

Multivariate Dyadic Regression Trees for Sparse Learning Problems NIPS 2010
Learning Networks of Stochastic Differential Equations NIPS 2010
A New Probabilistic Model for Rank Aggregation NIPS 2010
Heavy-Tailed Process Priors for Selective Shrinkage NIPS 2010
A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups NIPS 2010
A Family of Penalty Functions for Structured Sparsity NIPS 2010
Penalized Principal Component Regression on Graphs for Analysis of Subnetworks NIPS 2010
Graph-Valued Regression NIPS 2010
Scrambled Objects for Least-Squares Regression NIPS 2010
Exact learning curves for Gaussian process regression on large random graphs NIPS 2010
Adaptive Multi-Task Lasso: with Application to eQTL Detection NIPS 2010
Switched Latent Force Models for Movement Segmentation NIPS 2010
Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models NIPS 2010
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design JMLR 2010
Sparse Spectrum Gaussian Process Regression JMLR 2010
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity JMLR 2010
Stochastic Composite Likelihood JMLR 2010
High-dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency JMLR 2010
Restricted Eigenvalue Properties for Correlated Gaussian Designs JMLR 2010
Hierarchical Gaussian Process Regression ACML 2010
Model-based Boosting 2.0 JMLR 2010
Learning Nonlinear Dynamic Models from Non-sequenced Data AISTATS 2010
Variational Relevance Vector Machine for Tabular Data ACML 2010
Sparse Online Learning via Truncated Gradient JMLR 2009
Efficient Recovery of Jointly Sparse Vectors NIPS 2009