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Statistical Learning

4076 directly classified papers

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Papers

Tight conditions for consistent variable selection in high dimensional nonparametric regression COLT 2011
High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity NIPS 2011
Sequential Event Prediction with Association Rules COLT 2011
Universal low-rank matrix recovery from Pauli measurements NIPS 2011
Learning with the weighted trace-norm under arbitrary sampling distributions NIPS 2011
Noise Thresholds for Spectral Clustering NIPS 2011
High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions NIPS 2011
Linear-Time Estimators for Propensity Scores AISTATS 2011
On Learning Discrete Graphical Models using Group-Sparse Regularization AISTATS 2011
Asymptotic Theory for Linear-Chain Conditional Random Fields AISTATS 2011
Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure AISTATS 2011
Relational Learning with One Network: An Asymptotic Analysis AISTATS 2011
Generalization Bound for Infinitely Divisible Empirical Process AISTATS 2011
Mixability is Bayes Risk Curvature Relative to Log Loss COLT 2011
The Sample Complexity of Dictionary Learning COLT 2011
Information Rates and Optimal Decoding in Large Neural Populations NIPS 2011
Inductive reasoning about chimeric creatures NIPS 2011
Continuous-Time Regression Models for Longitudinal Networks NIPS 2011
A blind sparse deconvolution method for neural spike identification NIPS 2011
Sparsity Regret Bounds for Individual Sequences in Online Linear Regression COLT 2011
Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction NIPS 2011
Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NIPS 2011
Confidence Sets for Network Structure NIPS 2011
Structural equations and divisive normalization for energy-dependent component analysis NIPS 2011
How biased are maximum entropy models? NIPS 2011