Elkan, Charles

29 publications

MLHC 2017 Predicting Surgery Duration with Neural Heteroscedastic Regression Nathan H Ng, Rodney A Gabriel, Julian McAuley, Charles Elkan, Zachary C Lipton

ICLR 2016 Learning to Diagnose with LSTM Recurrent Neural Networks Zachary Chase Lipton, David C. Kale, Charles Elkan, Randall C. Wetzel

ECML-PKDD 2014 Nowcasting with Numerous Candidate Predictors Brendan Andrew Duncan, Charles Elkan

ECML-PKDD 2014 Optimal Thresholding of Classifiers to Maximize F1 Measure Zachary Chase Lipton, Charles Elkan, Balakrishnan Narayanaswamy

MLJ 2013 Beam Search Algorithms for Multilabel Learning Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan

MLJ 2013 Differential Privacy Based on Importance Weighting Zhanglong Ji, Charles Elkan

ECML-PKDD 2012 Learning and Inference in Probabilistic Classifier Chains with Beam Search Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan

ECML-PKDD 2012 Policy Iteration Based on a Learned Transition Model Vivek Ramavajjala, Charles Elkan

ICML 2012 Predicting Accurate Probabilities with a Ranking Loss Aditya Krishna Menon, Xiaoqian Jiang, Shankar Vembu, Charles Elkan, Lucila Ohno-Machado

ECML-PKDD 2011 Link Prediction via Matrix Factorization Aditya Krishna Menon, Charles Elkan

JMLR 2010 Quadratic Programming Feature Selection Irene Rodriguez-Lujan, Ramon Huerta, Charles Elkan, Carlos Santa Cruz

ICML 2009 Accounting for Burstiness in Topic Models Gabriel Doyle, Charles Elkan

ICML 2006 Clustering Documents with an Exponential-Family Approximation of the Dirichlet Compound Multinomial Distribution Charles Elkan

ICML 2005 Modeling Word Burstiness Using the Dirichlet Distribution Rasmus Elsborg Madsen, David Kauchak, Charles Elkan

JMLR 2004 Sources of Success for Boosted Wrapper Induction David Kauchak, Joseph Smarr, Charles Elkan

ECML-PKDD 2003 Learning Rules to Improve a Machine Translation System David Kauchak, Charles Elkan

NeurIPS 2003 Learning the K in K-Means Greg Hamerly, Charles Elkan

ICML 2003 Principled Methods for Advising Reinforcement Learning Agents Eric Wiewiora, Garrison W. Cottrell, Charles Elkan

ICML 2003 Using the Triangle Inequality to Accelerate K-Means Charles Elkan

ICML 2001 Bayesian Approaches to Failure Prediction for Disk Drives Greg Hamerly, Charles Elkan

ICML 2001 Obtaining Calibrated Probability Estimates from Decision Trees and Naive Bayesian Classifiers Bianca Zadrozny, Charles Elkan

IJCAI 2001 The Foundations of Cost-Sensitive Learning Charles Elkan

MLJ 1995 Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization Timothy L. Bailey, Charles Elkan

IJCAI 1993 Estimating the Accuracy of Learned Concepts Timothy L. Bailey, Charles Elkan

AAAI 1993 The Paradoxical Success of Fuzzy Logic Charles Elkan

MLJ 1991 A Critical Look at Experimental Evaluations of EBL Alberto M. Segre, Charles Elkan, Alexander Russell

IJCAI 1991 Measuring and Improving the Effectiveness of Representations Russell Greiner, Charles Elkan

AAAI 1990 Incremental, Approximate Planning Charles Elkan

IJCAI 1989 Conspiracy Numbers and Caching for Searching And/Or Trees and Theorem-Proving Charles Elkan