Charles Elkan

100 papers A* 26A 4B 1C 1Misc 3Journal 45Unranked 18
YearRankTypeTitle / Venue / Authors
2024 J jnl
Gamified crowd-sourcing of high-quality data for visual fine-tuning.
CoRR
Shashank Yadav, Rohan Tomar, Garvit Jain, Chirag Ahooja, Shubham Chaudhary, Charles Elkan
2021 J jnl
One-Class Remote Sensing Classification From Positive and Unlabeled Background Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.
Wenkai Li, Qinghua Guo, Charles Elkan
2019 Misc conf
A Modified Logistic Regression for Positive and Unlabeled Learning.
ACSSC
Kristen Jaskie, Charles Elkan, Andreas Spanias
2019 J jnl
SysML: The New Frontier of Machine Learning Systems.
CoRR
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. 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 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 Randall 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
2018 J jnl
Achieving Fluency and Coherency in Task-oriented Dialog.
CoRR
Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan
2018 — conf
What we need to learn if we want to do and not just talk.
NAACL-HLT (3)
Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan
2017 J jnl
End-to-End Offline Goal-Oriented Dialog Policy Learning via Policy Gradient.
CoRR
Li Zhou, Kevin Small, Oleg Rokhlenko, Charles Elkan
2017 — conf
Predicting Surgery Duration with Neural Heteroscedastic Regression.
MLHC
Nathan H. Ng, Rodney A. Gabriel, Julian J. McAuley, Charles Elkan, Zachary C. Lipton
2017 J jnl
Predicting Surgery Duration with Neural Heteroscedastic Regression.
CoRR
Nathan Ng, Rodney A. Gabriel, Julian J. McAuley, Charles Elkan, Zachary C. Lipton
2017 J jnl
Visualizing the Consequences of Evidence in Bayesian Networks.
CoRR
Clifford Champion, Charles Elkan
2016 A* conf
Learning to Diagnose with LSTM Recurrent Neural Networks.
ICLR (Poster)
Zachary Chase Lipton, David C. Kale, Charles Elkan, Randall C. Wetzel
2015 J jnl
Efficient Elastic Net Regularization for Sparse Linear Models.
CoRR
Zachary Chase Lipton, Charles Elkan
2015 — conf
Theory versus practice in data science.
ICSC
Charles Elkan
2014 J jnl
Differential Privacy and Machine Learning: a Survey and Review.
CoRR
Zhanglong Ji, Zachary Chase Lipton, Charles Elkan
2014 J jnl
F1-Optimal Thresholding in the Multi-Label Setting.
CoRR
Zachary Chase Lipton, Charles Elkan, Balakrishnan Narayanaswamy
2014 — conf
Learning to Re-rank for Interactive Problem Resolution and Query Refinement.
SIGDIAL Conference
Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan
2014 — conf
Nowcasting with Numerous Candidate Predictors.
ECML/PKDD (1)
Brendan Andrew Duncan, Charles Elkan
2014 — conf
Optimal Thresholding of Classifiers to Maximize F1 Measure.
ECML/PKDD (2)
Zachary Chase Lipton, Charles Elkan, Balakrishnan Narayanaswamy
2013 J jnl
Beam search algorithms for multilabel learning.
Mach. Learn.
Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan
2013 J jnl
Differential privacy based on importance weighting.
Mach. Learn.
Zhanglong Ji, Charles Elkan
2013 J jnl
Nonlinear support vector machines can systematically identify stocks with high and low future returns.
Algorithmic Finance
Ramón Huerta, Fernando J. Corbacho, Charles Elkan
2012 J jnl
Guest Editorial for Special Issue KDD'10.
ACM Trans. Knowl. Discov. Data
Charles Elkan, Yehuda Koren
2012 J jnl
Inhibition in Multiclass Classification.
Neural Comput.
Ramón Huerta, Shankar Vembu, José M. Amigó, Thomas Nowotny, Charles Elkan
2012 — conf
Learning and Inference in Probabilistic Classifier Chains with Beam Search.
ECML/PKDD (1)
Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan
2012 — conf
Policy Iteration Based on a Learned Transition Model.
ECML/PKDD (2)
Vivek Ramavajjala, Charles Elkan
2012 J jnl
Predicting accurate probabilities with a ranking loss
CoRR
Aditya Krishna Menon, Xiaoqian Jiang, Shankar Vembu, Charles Elkan, Lucila Ohno-Machado
2012 A* conf
Predicting accurate probabilities with a ranking loss.
ICML
Aditya Krishna Menon, Xiaoqian Jiang, Shankar Vembu, Charles Elkan, Lucila Ohno-Machado
2011 J jnl
A Positive and Unlabeled Learning Algorithm for One-Class Classification of Remote-Sensing Data.
IEEE Trans. Geosci. Remote. Sens.
Wenkai Li, Qinghua Guo, Charles Elkan
2011 J jnl
Fast Algorithms for Approximating the Singular Value Decomposition.
ACM Trans. Knowl. Discov. Data
Aditya Krishna Menon, Charles Elkan
2011 J jnl
Identifying Relevant Data for a Biological Database: Handcrafted Rules versus Machine Learning.
IEEE ACM Trans. Comput. Biol. Bioinform.
Aditya Kumar Sehgal, Sanmay Das, Keith Noto, Milton H. Saier Jr., Charles Elkan
2011 — conf
Link Prediction via Matrix Factorization.
ECML/PKDD (2)
Aditya Krishna Menon, Charles Elkan
2011 — conf
Reinforcement Learning with a Bilinear Q Function.
EWRL
Charles Elkan
2011 J jnl
The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text.
BMC Bioinform.
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 M. Rocha, Hagit Shatkay, Ashish V. Tendulkar, Shashank Agarwal, Feifan Liu, Xinglong Wang, Rafal Rak, Keith Noto, Charles Elkan, Zhiyong Lu
2010 A* conf
A Log-Linear Model with Latent Features for Dyadic Prediction.
ICDM
Aditya Krishna Menon, Charles Elkan
2010 A* conf
Conditional Random Fields for Word Hyphenation.
ACL
Nikolaos Trogkanis, Charles Elkan
2010 J jnl
Dyadic Prediction Using a Latent Feature Log-Linear Model
CoRR
Aditya Krishna Menon, Charles Elkan
2010 J jnl
Latent semantic indexing (LSI) fails for TREC collections.
SIGKDD Explor.
Avinash Atreya, Charles Elkan
2010 J jnl
Learning gene regulatory networks from only positive and unlabeled data.
BMC Bioinform.
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
2010 J jnl
Predicting labels for dyadic data.
Data Min. Knowl. Discov.
Aditya Krishna Menon, Charles Elkan
2010 — conf
Preserving Privacy in Data Mining via Importance Weighting.
PSDML
Charles Elkan
2010 J jnl
Quadratic Programming Feature Selection.
J. Mach. Learn. Res.
Irene Rodríguez-Luján, Ramón Huerta, Charles Elkan, Carlos Santa Cruz
2010 J jnl
Technical perspective - Creativity helps influence prediction precision.
Commun. ACM
Padhraic Smyth, Charles Elkan
2009 A* conf
Accounting for burstiness in topic models.
ICML
Gabriel Doyle, Charles Elkan
2009 J jnl
The Transporter Classification Database: recent advances.
Nucleic Acids Res.
Milton H. Saier Jr., Ming Ren Yen, Keith Noto, Dorjee G. Tamang, Charles Elkan
2008 A conf
Learning a two-stage SVM/CRF sequence classifier.
CIKM
Guilherme Hoefel, Charles Elkan
2008 A* conf
Learning classifiers from only positive and unlabeled data.
KDD
Charles Elkan, Keith Noto
2008 — conf
Learning to Find Relevant Biological Articles without Negative Training Examples.
Australasian Conference on Artificial Intelligence
Keith Noto, Milton H. Saier Jr., Charles Elkan
2007 — conf
Finding Transport Proteins in a General Protein Database.
PKDD
Sanmay Das, Milton H. Saier Jr., Charles Elkan
2007 J jnl
KDD Cup and workshop 2007.
SIGKDD Explor.
James Bennett, Charles Elkan, Bing Liu, Padhraic Smyth, Domonkos Tikk
2007 A* conf
Making generative classifiers robust to selection bias.
KDD
Andrew T. Smith, Charles Elkan
2006 A* conf
Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution.
ICML
Charles Elkan
2005 C conf
Deriving TF-IDF as a Fisher Kernel.
SPIRE
Charles Elkan
2005 J jnl
Fast Recognition of Musical Genres Using RBF Networks.
IEEE Trans. Knowl. Data Eng.
Douglas Turnbull, Charles Elkan
2005 A* conf
Modeling word burstiness using the Dirichlet distribution.
ICML
Rasmus Elsborg Madsen, David Kauchak, Charles Elkan
2004 A* conf
A Bayesian network framework for reject inference.
KDD
Andrew T. Smith, Charles Elkan
2004 J jnl
Sources of Success for Boosted Wrapper Induction.
J. Mach. Learn. Res.
David Kauchak, Joseph Smarr, Charles Elkan
2003 — conf
Learning Rules to Improve a Machine Translation System.
ECML
David Kauchak, Charles Elkan
2003 — conf
Learning the k in k-means.
NIPS
Greg Hamerly, Charles Elkan
2003 A* conf
Principled Methods for Advising Reinforcement Learning Agents.
ICML
Eric Wiewiora, Garrison W. Cottrell, Charles Elkan
2003 A* conf
Using the Triangle Inequality to Accelerate k-Means.
ICML
Charles Elkan
2002 A conf
Alternatives to the k-means algorithm that find better clusterings.
CIKM
Greg Hamerly, Charles Elkan
2002 J jnl
Improved disk-drive failure warnings.
IEEE Trans. Reliab.
Gordon F. Hughes, Joseph F. Murray, Kenneth Kreutz-Delgado, Charles Elkan
2002 A* conf
Transforming classifier scores into accurate multiclass probability estimates.
KDD
Bianca Zadrozny, Charles Elkan
2001 A* conf
Bayesian approaches to failure prediction for disk drives.
ICML
Greg Hamerly, Charles Elkan
2001 A* conf
Learning and making decisions when costs and probabilities are both unknown.
KDD
Bianca Zadrozny, Charles Elkan
2001 A* conf
Magical thinking in data mining: lessons from CoIL challenge 2000.
KDD
Charles Elkan
2001 A* conf
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers.
ICML
Bianca Zadrozny, Charles Elkan
2001 J jnl
Paradoxes of fuzzy logic, revisited.
Int. J. Approx. Reason.
Charles Elkan
2001 — conf
Shared challenges in data mining and computational biology (abstract of invited talk).
BIOKDD
Charles Elkan
2001 A* conf
The Foundations of Cost-Sensitive Learning.
IJCAI
Charles Elkan
2000 J jnl
KDD'99 Knowledge Discovery Contest.
SIGKDD Explor.
Charles Elkan
2000 J jnl
Results of the KDD'99 Classifier Learning.
SIGKDD Explor.
Charles Elkan
2000 J jnl
Scalability for Clustering Algorithms Revisited.
SIGKDD Explor.
Fredrik Farnstrom, James Lewis, Charles Elkan
1999 — ch.
MEME, MAST, and Meta-MEME: New Tools for Motif Discovery in Protein Sequences.
Pattern Discovery in Biomolecular Data
Timothy L. Bailey, Michael E. Baker, Charles Elkan, William Noble Grundy
1997 — conf
An Efficient Domain-Independent Algorithm for Detecting Approximately Duplicate Database Records.
DMKD
Alvaro E. Monge, Charles Elkan
1997 J jnl
Meta-MEME: motif-based hidden Markov models of protein families.
Comput. Appl. Biosci.
William Noble Grundy, Timothy L. Bailey, Charles Elkan, Michael E. Baker
1996 J jnl
Exploratory Analysis of Speedup Learning Data Using Epectation Maximization.
Artif. Intell.
Alberto Maria Segre, Geoffrey J. Gordon, Charles Elkan
1996 Misc conf
LPMEME: A Statistical Method for Inductive Logic Programming.
AI
Karan Bhatia, Charles Elkan
1996 J jnl
ParaMEME: a parallel implementation and a web interface for a DNA and protein motif discovery tool.
Comput. Appl. Biosci.
William Noble Grundy, Timothy L. Bailey, Charles Elkan
1996 Misc conf
Reasoning about Unknown, Counterfactual, and Nondeterministic Actions in First-Order Logic.
AI
Charles Elkan
1996 A* conf
The Field Matching Problem: Algorithms and Applications.
KDD
Alvaro E. Monge, Charles Elkan
1995 A conf
The Value of Prior Knowledge in Discovering Motifs with MEME.
ISMB
Timothy L. Bailey, Charles Elkan
1995 J jnl
Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization.
Mach. Learn.
Timothy L. Bailey, Charles Elkan
1994 J jnl
A High-Performance Explanation-Based Learning Algorithm.
Artif. Intell.
Alberto M. Segre, Charles Elkan
1994 J jnl
Elkan's Reply: The Paradoxical Controversy over Fuzzy Logic.
IEEE Expert
Charles Elkan
1994 A conf
Fitting a Mixture Model By Expectation Maximization To Discover Motifs In Biopolymer.
ISMB
Timothy L. Bailey, Charles Elkan
1994 J jnl
The Paradoxical Success of Fuzzy Logic.
IEEE Expert
Charles Elkan
1993 J jnl
D. B. Lenat and R. V. Guha, Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project.
Artif. Intell.
Charles Elkan, Russell Greiner
1993 A* conf
Estimating the Accuracy of Learned Concepts.
IJCAI
Timothy L. Bailey, Charles Elkan
1993 A* conf
The Paradoxical Success of Fuzzy Logic.
AAAI
Charles Elkan
1991 J jnl
A Critical Look at Experimental Evaluations of EBL.
Mach. Learn.
Alberto M. Segre, Charles Elkan, Alexander Russell
1991 A* conf
Measuring and Improving the Effectiveness of Representations.
IJCAI
Russell Greiner, Charles Elkan
1990 J jnl
A Rational Reconstruction of Nonmonotonic Truth Maintenance Systems.
Artif. Intell.
Charles Elkan
1990 — —
Automated Inductive Reasoning about Logic Programs.
Charles Elkan
1990 A* conf
Incremental, Approximate Planning.
AAAI
Charles Elkan
1990 A* conf
Independence of Logic Database Queries and Updates.
PODS
Charles Elkan
1989 A* conf
A Decision Procedure for Conjunctive Query Disjointness.
PODS
Charles Elkan
1989 A* conf
Conspiracy Numbers and Caching for Searching And/Or Trees and Theorem-Proving.
IJCAI
Charles Elkan
1989 B conf
Logical Characterizations of Nonmonotonic TMSs.
MFCS
Charles Elkan
1988 — conf
Automated Inductive Reasoning about Logic Programs.
ICLP/SLP
Charles Elkan, David A. McAllester