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Statistical Learning

4,117 papers

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Papers

Non-rigid point set registration: Coherent Point Drift NIPS 2006
Active learning for misspecified generalized linear models NIPS 2006
Tighter PAC-Bayes Bounds NIPS 2006
PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NIPS 2006
High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression NIPS 2006
An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments NIPS 2006
Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds NIPS 2006
PG-means: learning the number of clusters in data NIPS 2006
AdaBoost is Consistent NIPS 2006
An Information Theoretic Framework for Eukaryotic Gradient Sensing NIPS 2006
An Oracle Inequality for Clipped Regularized Risk Minimizers NIPS 2006
On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts NIPS 2006
A Kernel Method for the Two-Sample-Problem NIPS 2006
A PAC-Bayes Risk Bound for General Loss Functions NIPS 2006
Bounds for Linear Multi-Task Learning JMLR 2006
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals JMLR 2006
Some Discriminant-Based PAC Algorithms JMLR 2006
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting JMLR 2006
Learning Coordinate Covariances via Gradients JMLR 2006
Learning Minimum Volume Sets JMLR 2006
Some Theory for Generalized Boosting Algorithms JMLR 2006
Consistency and Convergence Rates of One-Class SVMs and Related Algorithms JMLR 2006
Segmental Hidden Markov Models with Random Effects for Waveform Modeling JMLR 2006
Lower Bounds and Aggregation in Density Estimation JMLR 2006
Quantile Regression Forests JMLR 2006