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Regression

5,004 papers

Papers per year

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Papers

From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models NIPS 2011
Robust Lasso with missing and grossly corrupted observations NIPS 2011
Gaussian Process Training with Input Noise NIPS 2011
Unifying Framework for Fast Learning Rate of Non-Sparse Multiple Kernel Learning NIPS 2011
High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity NIPS 2011
Greedy Model Averaging NIPS 2011
Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation NIPS 2011
Statistical Performance of Convex Tensor Decomposition NIPS 2011
Sparse Features for PCA-Like Linear Regression NIPS 2011
Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning NIPS 2011
Semi-supervised Regression via Parallel Field Regularization NIPS 2011
Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NIPS 2011
Sparse recovery by thresholded non-negative least squares NIPS 2011
A blind sparse deconvolution method for neural spike identification NIPS 2011
On the accuracy of l1-filtering of signals with block-sparse structure NIPS 2011
TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning NIPS 2011
Submodular Multi-Label Learning NIPS 2011
Approximate Model Selection for Large Scale LSSVM ACML 2011
Estimating Diffusion Probability Changes for AsIC-SIS Model from Information Diffusion Results ACML 2011
Group Orthogonal Matching Pursuit for Logistic Regression AISTATS 2011
CAKE: Convex Adaptive Kernel Density Estimation AISTATS 2011
Estimating Probabilities in Recommendation Systems AISTATS 2011
Tight conditions for consistent variable selection in high dimensional nonparametric regression COLT 2011
Optimal aggregation of affine estimators COLT 2011
Regression on Fixed-Rank Positive Semidefinite Matrices: A Riemannian Approach JMLR 2011