Charles Elkan

Publication Activity (10 Years)

Years Active: 1988-2021
Publications (10 Years): 10

Top Topics

Differential Privacy

Multiclass Classification

Top Venues

Publications

Wenkai Li, Qinghua Guo, Charles Elkan
One-Class Remote Sensing Classification From Positive and Unlabeled Background Data. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14 (2021)
Kristen Jaskie, Charles Elkan, Andreas Spanias
A Modified Logistic Regression for Positive and Unlabeled Learning. ACSSC (2019)
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan R. Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar
SysML: The New Frontier of Machine Learning Systems. CoRR (2019)
Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan
Achieving Fluency and Coherency in Task-oriented Dialog. CoRR (2018)
Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan
What we need to learn if we want to do and not just talk. NAACL-HLT (3) (2018)
Nathan H. Ng, Rodney A. Gabriel, Julian J. McAuley, Charles Elkan, Zachary C. Lipton
Predicting Surgery Duration with Neural Heteroscedastic Regression. MLHC (2017)
Nathan Ng, Rodney A. Gabriel, Julian J. McAuley, Charles Elkan, Zachary C. Lipton
Predicting Surgery Duration with Neural Heteroscedastic Regression. CoRR (2017)
Li Zhou, Kevin Small, Oleg Rokhlenko, Charles Elkan
End-to-End Offline Goal-Oriented Dialog Policy Learning via Policy Gradient. CoRR (2017)
Clifford Champion, Charles Elkan
Visualizing the Consequences of Evidence in Bayesian Networks. CoRR (2017)
Zachary Chase Lipton, David C. Kale, Charles Elkan, Randall C. Wetzel
Learning to Diagnose with LSTM Recurrent Neural Networks. ICLR (Poster) (2016)
Zachary Chase Lipton, Charles Elkan
Efficient Elastic Net Regularization for Sparse Linear Models. CoRR (2015)
Charles Elkan
Theory versus practice in data science. ICSC (2015)
Zachary Chase Lipton, Charles Elkan, Balakrishnan Narayanaswamy
F1-Optimal Thresholding in the Multi-Label Setting. CoRR (2014)
Zhanglong Ji, Zachary Chase Lipton, Charles Elkan
Differential Privacy and Machine Learning: a Survey and Review. CoRR (2014)
Zachary Chase Lipton, Charles Elkan, Balakrishnan Narayanaswamy
Optimal Thresholding of Classifiers to Maximize F1 Measure. ECML/PKDD (2) (2014)
Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan
Learning to Re-rank for Interactive Problem Resolution and Query Refinement. SIGDIAL Conference (2014)
Brendan Duncan, Charles Elkan
Nowcasting with Numerous Candidate Predictors. ECML/PKDD (1) (2014)
Ramón Huerta, Fernando J. Corbacho, Charles Elkan
Nonlinear support vector machines can systematically identify stocks with high and low future returns. Algorithmic Finance 2 (1) (2013)
Zhanglong Ji, Charles Elkan
Differential privacy based on importance weighting. Mach. Learn. 93 (1) (2013)
Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan
Beam search algorithms for multilabel learning. Mach. Learn. 92 (1) (2013)
Aditya Krishna Menon, Xiaoqian Jiang, Shankar Vembu, Charles Elkan, Lucila Ohno-Machado
Predicting accurate probabilities with a ranking loss CoRR (2012)
Ramón Huerta, Shankar Vembu, José M. Amigó, Thomas Nowotny, Charles Elkan
Inhibition in Multiclass Classification. Neural Comput. 24 (9) (2012)
Vivek Ramavajjala, Charles Elkan
Policy Iteration Based on a Learned Transition Model. ECML/PKDD (2) (2012)
Charles Elkan, Yehuda Koren
Guest Editorial for Special Issue KDD'10. ACM Trans. Knowl. Discov. Data 5 (4) (2012)
Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan
Learning and Inference in Probabilistic Classifier Chains with Beam Search. ECML/PKDD (1) (2012)
Aditya Krishna Menon, Xiaoqian Jiang, Shankar Vembu, Charles Elkan, Lucila Ohno-Machado
Predicting accurate probabilities with a ranking loss. ICML (2012)
Wenkai Li, Qinghua Guo, Charles Elkan
A Positive and Unlabeled Learning Algorithm for One-Class Classification of Remote-Sensing Data. IEEE Trans. Geosci. Remote. Sens. 49 (2) (2011)
Martin Krallinger, Miguel Vazquez, Florian Leitner, David Salgado, Andrew Chatr-aryamontri, Andrew G. Winter, Livia Perfetto, Leonardo Briganti, Luana Licata, Marta Iannuccelli, Luisa Castagnoli, Gianni Cesareni, Mike Tyers, Gerold Schneider, Fabio Rinaldi, Robert Leaman, Graciela Gonzalez, Sérgio Matos, Sun Kim, W. John Wilbur, Luis Mateus Rocha, Hagit Shatkay, Ashish V. Tendulkar, Shashank Agarwal, Feifan Liu, Xinglong Wang, Rafal Rak, Keith Noto, Charles Elkan, Zhiyong Lu
The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text. BMC Bioinform. 12 (S-8) (2011)
Charles Elkan
Reinforcement Learning with a Bilinear Q Function. EWRL (2011)
Aditya Krishna Menon, Charles Elkan
Fast Algorithms for Approximating the Singular Value Decomposition. ACM Trans. Knowl. Discov. Data 5 (2) (2011)
Aditya Kumar Sehgal, Sanmay Das, Keith Noto, Milton H. Saier Jr., Charles Elkan
Identifying Relevant Data for a Biological Database: Handcrafted Rules versus Machine Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 8 (3) (2011)
Aditya Krishna Menon, Charles Elkan
Link Prediction via Matrix Factorization. ECML/PKDD (2) (2011)
Aditya Krishna Menon, Charles Elkan
A Log-Linear Model with Latent Features for Dyadic Prediction. ICDM (2010)
Avinash Atreya, Charles Elkan
Latent semantic indexing (LSI) fails for TREC collections. SIGKDD Explor. 12 (2) (2010)
Nikolaos Trogkanis, Charles Elkan
Conditional Random Fields for Word Hyphenation. ACL (2010)
Irene Rodríguez-Luján, Ramón Huerta, Charles Elkan, Carlos Santa Cruz
Quadratic Programming Feature Selection. J. Mach. Learn. Res. 11 (2010)
Padhraic Smyth, Charles Elkan
Technical perspective - Creativity helps influence prediction precision. Commun. ACM 53 (4) (2010)
Charles Elkan
Preserving Privacy in Data Mining via Importance Weighting. PSDML (2010)
Aditya Krishna Menon, Charles Elkan
Dyadic Prediction Using a Latent Feature Log-Linear Model CoRR (2010)
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
Learning gene regulatory networks from only positive and unlabeled data. BMC Bioinform. 11 (2010)
Aditya Krishna Menon, Charles Elkan
Predicting labels for dyadic data. Data Min. Knowl. Discov. 21 (2) (2010)
Gabriel Doyle, Charles Elkan
Accounting for burstiness in topic models. ICML (2009)
Milton H. Saier Jr., Ming Ren Yen, Keith Noto, Dorjee G. Tamang, Charles Elkan
The Transporter Classification Database: recent advances. Nucleic Acids Res. 37 (Database-Issue) (2009)
Guilherme Hoefel, Charles Elkan
Learning a two-stage SVM/CRF sequence classifier. CIKM (2008)
Charles Elkan, Keith Noto
Learning classifiers from only positive and unlabeled data. KDD (2008)
Keith Noto, Milton H. Saier Jr., Charles Elkan
Learning to Find Relevant Biological Articles without Negative Training Examples. Australasian Conference on Artificial Intelligence (2008)
Sanmay Das, Milton H. Saier Jr., Charles Elkan
Finding Transport Proteins in a General Protein Database. PKDD (2007)
Andrew T. Smith, Charles Elkan
Making generative classifiers robust to selection bias. KDD (2007)
James Bennett, Charles Elkan, Bing Liu, Padhraic Smyth, Domonkos Tikk
KDD Cup and workshop 2007. SIGKDD Explor. 9 (2) (2007)
Charles Elkan
Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution. ICML (2006)
Rasmus Elsborg Madsen, David Kauchak, Charles Elkan
Modeling word burstiness using the Dirichlet distribution. ICML (2005)
Charles Elkan
Deriving TF-IDF as a Fisher Kernel. SPIRE (2005)
Douglas Turnbull, Charles Elkan
Fast Recognition of Musical Genres Using RBF Networks. IEEE Trans. Knowl. Data Eng. 17 (4) (2005)
David Kauchak, Joseph Smarr, Charles Elkan
Sources of Success for Boosted Wrapper Induction. J. Mach. Learn. Res. 5 (2004)
Andrew T. Smith, Charles Elkan
A Bayesian network framework for reject inference. KDD (2004)
David Kauchak, Charles Elkan
Learning Rules to Improve a Machine Translation System. ECML (2003)
Eric Wiewiora, Garrison W. Cottrell, Charles Elkan
Principled Methods for Advising Reinforcement Learning Agents. ICML (2003)
Greg Hamerly, Charles Elkan
Learning the k in k-means. NIPS (2003)
Charles Elkan
Using the Triangle Inequality to Accelerate k-Means. ICML (2003)
Gordon F. Hughes, Joseph F. Murray, Kenneth Kreutz-Delgado, Charles Elkan
Improved disk-drive failure warnings. IEEE Trans. Reliab. 51 (3) (2002)
Bianca Zadrozny, Charles Elkan
Transforming classifier scores into accurate multiclass probability estimates. KDD (2002)
Greg Hamerly, Charles Elkan
Alternatives to the k-means algorithm that find better clusterings. CIKM (2002)
Bianca Zadrozny, Charles Elkan
Learning and making decisions when costs and probabilities are both unknown. KDD (2001)
Charles Elkan
Shared challenges in data mining and computational biology (abstract of invited talk). BIOKDD (2001)
Charles Elkan
The Foundations of Cost-Sensitive Learning. IJCAI (2001)
Bianca Zadrozny, Charles Elkan
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers. ICML (2001)
Greg Hamerly, Charles Elkan
Bayesian approaches to failure prediction for disk drives. ICML (2001)
Charles Elkan
Paradoxes of fuzzy logic, revisited. Int. J. Approx. Reason. 26 (2) (2001)
Charles Elkan
Magical thinking in data mining: lessons from CoIL challenge 2000. KDD (2001)
Charles Elkan
KDD'99 Knowledge Discovery Contest. SIGKDD Explor. 1 (2) (2000)
Charles Elkan
Results of the KDD'99 Classifier Learning. SIGKDD Explor. 1 (2) (2000)
Fredrik Farnstrom, James Lewis, Charles Elkan
Scalability for Clustering Algorithms Revisited. SIGKDD Explor. 2 (1) (2000)
Alvaro E. Monge, Charles Elkan
An Efficient Domain-Independent Algorithm for Detecting Approximately Duplicate Database Records. DMKD (1997)
William Noble Grundy, Timothy L. Bailey, Charles Elkan, Michael E. Baker
Meta-MEME: motif-based hidden Markov models of protein families. Comput. Appl. Biosci. 13 (4) (1997)
William Noble Grundy, Timothy L. Bailey, Charles Elkan
ParaMEME: a parallel implementation and a web interface for a DNA and protein motif discovery tool. Comput. Appl. Biosci. 12 (4) (1996)
Karan Bhatia, Charles Elkan
LPMEME: A Statistical Method for Inductive Logic Programming. Canadian Conference on AI (1996)
Alberto Maria Segre, Geoffrey J. Gordon, Charles Elkan
Exploratory Analysis of Speedup Learning Data Using Epectation Maximization. Artif. Intell. 85 (1-2) (1996)
Alvaro E. Monge, Charles Elkan
The Field Matching Problem: Algorithms and Applications. KDD (1996)
Charles Elkan
Reasoning about Unknown, Counterfactual, and Nondeterministic Actions in First-Order Logic. Canadian Conference on AI (1996)
Timothy L. Bailey, Charles Elkan
Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization. Mach. Learn. 21 (1-2) (1995)
Timothy L. Bailey, Charles Elkan
The Value of Prior Knowledge in Discovering Motifs with MEME. ISMB (1995)
Timothy L. Bailey, Charles Elkan
Fitting a Mixture Model By Expectation Maximization To Discover Motifs In Biopolymer. ISMB (1994)
Charles Elkan
The Paradoxical Success of Fuzzy Logic. IEEE Expert 9 (4) (1994)
Alberto M. Segre, Charles Elkan
A High-Performance Explanation-Based Learning Algorithm. Artif. Intell. 69 (1-2) (1994)
Charles Elkan
Elkan's Reply: The Paradoxical Controversy over Fuzzy Logic. IEEE Expert 9 (4) (1994)
Charles Elkan, Russell Greiner
D. B. Lenat and R. V. Guha, Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project. Artif. Intell. 61 (1) (1993)
Timothy L. Bailey, Charles Elkan
Estimating the Accuracy of Learned Concepts. IJCAI (1993)
Charles Elkan
The Paradoxical Success of Fuzzy Logic. AAAI (1993)
Alberto M. Segre, Charles Elkan, Alexander Russell
A Critical Look at Experimental Evaluations of EBL. Mach. Learn. 6 (1991)
Russell Greiner, Charles Elkan
Measuring and Improving the Effectiveness of Representations. IJCAI (1991)
Charles Elkan
Incremental, Approximate Planning. AAAI (1990)
Charles Elkan
A Rational Reconstruction of Nonmonotonic Truth Maintenance Systems. Artif. Intell. 43 (2) (1990)
Charles Elkan
Independence of Logic Database Queries and Updates. PODS (1990)
Charles Elkan
A Decision Procedure for Conjunctive Query Disjointness. PODS (1989)
Charles Elkan
Conspiracy Numbers and Caching for Searching And/Or Trees and Theorem-Proving. IJCAI (1989)
Charles Elkan
Logical Characterizations of Nonmonotonic TMSs. MFCS (1989)
Charles Elkan, David A. McAllester
Automated Inductive Reasoning about Logic Programs. ICLP/SLP (1988)