Benjamin Taskar

25 papers A* 9A 2Journal 3Unranked 11
YearRankTypeTitle / Venue / Authors
2014 — conf
Expectation-Maximization for Learning Determinantal Point Processes.
NIPS
Jennifer Gillenwater, Alex Kulesza, Emily B. Fox, Benjamin Taskar
2014 A* conf
Learning the Parameters of Determinantal Point Process Kernels.
ICML
Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams, Benjamin Taskar
2011 J jnl
Controlling Complexity in Part-of-Speech Induction.
J. Artif. Intell. Res.
João Graça, Kuzman Ganchev, Luísa Coheur, Fernando Pereira, Benjamin Taskar
2010 A conf
Structured Prediction Cascades.
AISTATS
David J. Weiss, Benjamin Taskar
2009 A* conf
Learning from ambiguously labeled images.
CVPR
Timothée Cour, Benjamin Sapp, Chris Jordan, Benjamin Taskar
2007 A* conf
A permutation-augmented sampler for DP mixture models.
ICML
Percy Liang, Michael I. Jordan, Benjamin Taskar
2006 — conf
Alignment by Agreement.
HLT-NAACL
Percy Liang, Benjamin Taskar, Dan Klein
2006 A* conf
An End-to-End Discriminative Approach to Machine Translation.
ACL
Percy Liang, Alexandre Bouchard-Côté, Dan Klein, Benjamin Taskar
2006 J jnl
Structured Prediction, Dual Extragradient and Bregman Projections.
J. Mach. Learn. Res.
Benjamin Taskar, Simon Lacoste-Julien, Michael I. Jordan
2006 — conf
Word Alignment via Quadratic Assignment.
HLT-NAACL
Simon Lacoste-Julien, Benjamin Taskar, Dan Klein, Michael I. Jordan
2005 — conf
A Discriminative Matching Approach to Word Alignment.
HLT/EMNLP
Benjamin Taskar, Simon Lacoste-Julien, Dan Klein
2005 — conf
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data.
CVPR (2)
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz, Andrew Y. Ng
2005 A* conf
Learning structured prediction models: a large margin approach.
ICML
Benjamin Taskar, Vassil Chatalbashev, Daphne Koller, Carlos Guestrin
2005 — conf
Structured Prediction via the Extragradient Method.
NIPS
Benjamin Taskar, Simon Lacoste-Julien, Michael I. Jordan
2004 — conf
Exponentiated Gradient Algorithms for Large-margin Structured Classification.
NIPS
Peter L. Bartlett, Michael Collins, Benjamin Taskar, David A. McAllester
2004 A* conf
Learning associative Markov networks.
ICML
Benjamin Taskar, Vassil Chatalbashev, Daphne Koller
2003 A* conf
Learning on the Test Data: Leveraging Unseen Features.
ICML
Benjamin Taskar, Ming Fai Wong, Daphne Koller
2003 — conf
Link Prediction in Relational Data.
NIPS
Benjamin Taskar, Ming Fai Wong, Pieter Abbeel, Daphne Koller
2003 — conf
Max-Margin Markov Networks.
NIPS
Benjamin Taskar, Carlos Guestrin, Daphne Koller
2002 A conf
Discriminative Probabilistic Models for Relational Data.
UAI
Benjamin Taskar, Pieter Abbeel, Daphne Koller
2002 J jnl
Learning Probabilistic Models of Link Structure.
J. Mach. Learn. Res.
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar
2001 A* conf
Learning Probabilistic Models of Relational Structure.
ICML
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar
2001 A* conf
Probabilistic Classification and Clustering in Relational Data.
IJCAI
Benjamin Taskar, Eran Segal, Daphne Koller
2001 — conf
Rich probabilistic models for gene expression.
ISMB (Supplement of Bioinformatics)
Eran Segal, Benjamin Taskar, Audrey P. Gasch, Nir Friedman, Daphne Koller
2001 — conf
Selectivity Estimation using Probabilistic Models.
SIGMOD Conference
Lise Getoor, Benjamin Taskar, Daphne Koller