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Regression

5,004 papers

Papers per year

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Papers

On the Representer Theorem and Equivalent Degrees of Freedom of SVR JMLR 2007
Hierarchical Average Reward Reinforcement Learning JMLR 2007
Stagewise Lasso JMLR 2007
A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning JMLR 2007
Predicting Partial Paths from Planning Problem Parameters RSS 2007
Adaptive Non-Stationary Kernel Regression for Terrain Modeling RSS 2007
Ordinal Regression by Extended Binary Classification NIPS 2006
Predicting spike times from subthreshold dynamics of a neuron NIPS 2006
Learning from Multiple Sources NIPS 2006
Bayesian Ensemble Learning NIPS 2006
Logistic Regression for Single Trial EEG Classification NIPS 2006
Large-Scale Sparsified Manifold Regularization NIPS 2006
A Scalable Machine Learning Approach to Go NIPS 2006
Optimal Change-Detection and Spiking Neurons NIPS 2006
On Transductive Regression NIPS 2006
Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis NIPS 2006
Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space NIPS 2006
A Humanlike Predictor of Facial Attractiveness NIPS 2006
Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype NIPS 2006
Mixture Regression for Covariate Shift NIPS 2006
Learning Motion Style Synthesis from Perceptual Observations NIPS 2006
Nonlinear physically-based models for decoding motor-cortical population activity NIPS 2006
Unsupervised Regression with Applications to Nonlinear System Identification NIPS 2006
Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error JMLR 2006
Learning Coordinate Covariances via Gradients JMLR 2006