Papers
4,122 papers found
Margin Trees for High-dimensional Classification
Robert Tibshirani, Trevor Hastie
Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling
Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
Measuring Differentiability: Unmasking Pseudonymous Authors
Moshe Koppel, Jonathan Schler, Elisheva Bonchek-Dokow
Minimax Regret Classifier for Imprecise Class Distributions
Rocío Alaiz-Rodríguez, Alicia Guerrero-Curieses, Jesús Cid-Sueiro
Multi-class Protein Classification Using Adaptive Codes
Iain Melvin, Eugene Ie, Jason Weston et al.
Multi-Task Learning for Classification with Dirichlet Process Priors
Ya Xue, Xuejun Liao, Lawrence Carin et al.
Noise Tolerant Variants of the Perceptron Algorithm
Roni Khardon, Gabriel Wachman
Nonlinear Boosting Projections for Ensemble Construction
Nicolás García-Pedrajas, César García-Osorio, Colin Fyfe
Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections
Ping Li, Trevor J. Hastie, Kenneth W. Church
Online Learning of Multiple Tasks with a Shared Loss
Ofer Dekel, Philip M. Long, Yoram Singer
On the Consistency of Multiclass Classification Methods
Ambuj Tewari, Peter L. Bartlett
On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning
Rie Johnson, Tong Zhang
On the Representer Theorem and Equivalent Degrees of Freedom of SVR
Francesco Dinuzzo, Marta Neve, Giuseppe De Nicolao et al.
PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers
François Laviolette, Mario Marchand
Penalized Model-Based Clustering with Application to Variable Selection
Wei Pan, Xiaotong Shen
Polynomial Identification in the Limit of Substitutable Context-free Languages
Alexander Clark, Rémi Eyraud
Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters
Gavin C. Cawley, Nicola L. C. Talbot
Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes
Sridhar Mahadevan, Mauro Maggioni
Ranking the Best Instances
Stéphan Clémençon, Nicolas Vayatis
Refinable Kernels
Yuesheng Xu, Haizhang Zhang
Relational Dependency Networks
Jennifer Neville, David Jensen
Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data
Zakria Hussain, François Laviolette, Mario Marchand et al.
Separating Models of Learning from Correlated and Uncorrelated Data
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio et al.
Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results
Peter L. Bartlett, Ambuj Tewari
Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification
Onur C. Hamsici, Aleix M. Martinez