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ORCIDBen Taskar
Benjamin Taskar
Person information
- affiliation: University of Washington, Computer Science and Engineering, USA
- affiliation: University of Pennsylvania, Department of Computer and Information Science, USA
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Books and Theses
- 2005
[b1]Ben Taskar:
Learning structured prediction models : a large margin approach. Stanford University, USA, 2005
Journal Articles
- 2017
- [j14]Min Sun, Ali Farhadi, Ben Taskar, Steven M. Seitz:
Summarizing Unconstrained Videos Using Salient Montages. IEEE Trans. Pattern Anal. Mach. Intell. 39(11): 2256-2269 (2017) - 2014
- [j13]Edward A. Lee, Björn Hartmann, John Kubiatowicz, Tajana Simunic Rosing, John Wawrzynek, David Wessel, Jan M. Rabaey, Kris Pister, Alberto L. Sangiovanni-Vincentelli
, Sanjit A. Seshia, David T. Blaauw, Prabal Dutta, Kevin Fu, Carlos Guestrin, Ben Taskar, Roozbeh Jafari, Douglas L. Jones, Vijay Kumar, Rahul Mangharam, George J. Pappas, Richard M. Murray, Anthony Rowe:
The Swarm at the Edge of the Cloud. IEEE Des. Test 31(3): 8-20 (2014) - 2012
- [j12]Alex Kulesza, Ben Taskar:
Determinantal Point Processes for Machine Learning. Found. Trends Mach. Learn. 5(2-3): 123-286 (2012) - [j11]Alexander Toshev, Ben Taskar, Kostas Daniilidis:
Shape-Based Object Detection via Boundary Structure Segmentation. Int. J. Comput. Vis. 99(2): 123-146 (2012) - [j10]Nematollah Batmanghelich, Ben Taskar, Christos Davatzikos:
Generative-Discriminative Basis Learning for Medical Imaging. IEEE Trans. Medical Imaging 31(1): 51-69 (2012) - 2011
- [j9]João Graça, Kuzman Ganchev, Luísa Coheur, Fernando Pereira, Benjamin Taskar:
Controlling Complexity in Part-of-Speech Induction. J. Artif. Intell. Res. 41: 527-551 (2011) - [j8]Jennifer Gillenwater, Kuzman Ganchev, João Graça, Fernando Pereira, Ben Taskar:
Posterior Sparsity in Unsupervised Dependency Parsing. J. Mach. Learn. Res. 12: 455-490 (2011) - [j7]Timothée Cour, Benjamin Sapp, Ben Taskar:
Learning from Partial Labels. J. Mach. Learn. Res. 12: 1501-1536 (2011) - 2010
- [j6]João Graça, Kuzman Ganchev, Ben Taskar:
Learning Tractable Word Alignment Models with Complex Constraints. Comput. Linguistics 36(3): 481-504 (2010) - [j5]Kuzman Ganchev, João Graça, Jennifer Gillenwater, Ben Taskar:
Posterior Regularization for Structured Latent Variable Models. J. Mach. Learn. Res. 11: 2001-2049 (2010) - [j4]Guillaume Obozinski, Ben Taskar, Michael I. Jordan:
Joint covariate selection and joint subspace selection for multiple classification problems. Stat. Comput. 20(2): 231-252 (2010) - 2009
- [j3]João Graça, Kuzman Ganchev, Ben Taskar:
PostCAT - Posterior Constrained Alignment Toolkit. Prague Bull. Math. Linguistics 91: 27-36 (2009) - 2006
- [j2]Benjamin Taskar, Simon Lacoste-Julien, Michael I. Jordan:
Structured Prediction, Dual Extragradient and Bregman Projections. J. Mach. Learn. Res. 7: 1627-1653 (2006) - 2002
- [j1]Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar:
Learning Probabilistic Models of Link Structure. J. Mach. Learn. Res. 3: 679-707 (2002)
Conference and Workshop Papers
- 2015
- [c67]Tianqi Chen, Sameer Singh, Ben Taskar, Carlos Guestrin:
Efficient Second-Order Gradient Boosting for Conditional Random Fields. AISTATS 2015 - 2014
- [c66]Ben London, Bert Huang, Ben Taskar, Lise Getoor:
PAC-Bayesian Collective Stability. AISTATS 2014: 585-594 - [c65]Qiao Zhang, Shyamnath Gollakota, Ben Taskar, Raj P. N. Rao:
Non-intrusive tongue machine interface. CHI 2014: 2555-2558 - [c64]Andrea Vedaldi, Siddharth Mahendran, Stavros Tsogkas, Subhransu Maji, Ross B. Girshick, Juho Kannala, Esa Rahtu, Iasonas Kokkinos, Matthew B. Blaschko, David J. Weiss, Ben Taskar, Karen Simonyan, Naomi Saphra, Sammy Mohamed:
Understanding Objects in Detail with Fine-Grained Attributes. CVPR 2014: 3622-3629 - [c63]Min Sun, Ali Farhadi, Ben Taskar, Steven M. Seitz:
Salient Montages from Unconstrained Videos. ECCV (7) 2014: 472-488 - [c62]Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams, Benjamin Taskar:
Learning the Parameters of Determinantal Point Process Kernels. ICML 2014: 1224-1232 - [c61]Jennifer Gillenwater, Alex Kulesza, Emily B. Fox, Benjamin Taskar:
Expectation-Maximization for Learning Determinantal Point Processes. NIPS 2014: 3149-3157 - 2013
- [c60]Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox, Ben Taskar:
Nystrom Approximation for Large-Scale Determinantal Processes. AISTATS 2013: 85-98 - [c59]Luheng He, Jennifer Gillenwater, Ben Taskar:
Graph-Based Posterior Regularization for Semi-Supervised Structured Prediction. CoNLL 2013: 38-46 - [c58]David J. Weiss, Ben Taskar:
SCALPEL: Segmentation Cascades with Localized Priors and Efficient Learning. CVPR 2013: 2035-2042 - [c57]Benjamin Sapp, Ben Taskar:
MODEC: Multimodal Decomposable Models for Human Pose Estimation. CVPR 2013: 3674-3681 - [c56]Ofir Pele, Ben Taskar:
The Tangent Earth Mover's Distance. GSI 2013: 397-404 - [c55]David J. Weiss, Benjamin Sapp, Ben Taskar:
Dynamic Structured Model Selection. ICCV 2013: 2656-2663 - [c54]Ofir Pele, Ben Taskar, Amir Globerson, Michael Werman:
The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification. ICML (1) 2013: 205-213 - [c53]Ben London, Bert Huang, Ben Taskar, Lise Getoor:
Collective Stability in Structured Prediction: Generalization from One Example. ICML (3) 2013: 828-836 - [c52]David J. Weiss, Ben Taskar:
Learning Adaptive Value of Information for Structured Prediction. NIPS 2013: 953-961 - [c51]Raja Hafiz Affandi, Emily B. Fox, Ben Taskar:
Approximate Inference in Continuous Determinantal Processes. NIPS 2013: 1430-1438 - 2012
- [c50]Jennifer Gillenwater, Alex Kulesza, Ben Taskar:
Discovering Diverse and Salient Threads in Document Collections. EMNLP-CoNLL 2012: 710-720 - [c49]Shen Li, João Graça, Ben Taskar:
Wiki-ly Supervised Part-of-Speech Tagging. EMNLP-CoNLL 2012: 1389-1398 - [c48]Jennifer Gillenwater, Alex Kulesza, Ben Taskar:
Near-Optimal MAP Inference for Determinantal Point Processes. NIPS 2012: 2744-2752 - 2011
- [c47]Benjamin Sapp, David J. Weiss, Ben Taskar:
Parsing human motion with stretchable models. CVPR 2011: 1281-1288 - [c46]Alex Kulesza, Ben Taskar:
k-DPPs: Fixed-Size Determinantal Point Processes. ICML 2011: 1193-1200 - [c45]Kayhan N. Batmanghelich, Dong Hye Ye, Kilian M. Pohl, Ben Taskar, Christos Davatzikos:
Disease classification and prediction via semi-supervised dimensionality reduction. ISBI 2011: 1086-1090 - [c44]Nematollah Batmanghelich, Aoyan Dong, Ben Taskar, Christos Davatzikos:
Regularized Tensor Factorization for Multi-Modality Medical Image Classification. MICCAI (3) 2011: 17-24 - [c43]Alex Kulesza, Ben Taskar:
Learning Determinantal Point Processes. UAI 2011: 419-427 - 2010
- [c42]Jennifer Gillenwater, Kuzman Ganchev, João Graça, Fernando Pereira, Ben Taskar:
Sparsity in Dependency Grammar Induction. ACL (2) 2010: 194-199 - [c41]Nematollah Batmanghelich, Ali Gooya, Stathis Kanterakis, Ben Taskar, Christos Davatzikos:
Application of trace-norm and low-rank matrix decomposition for computational anatomy. CVPR Workshops 2010: 146-153 - [c40]Alexander Toshev, Philippos Mordohai, Ben Taskar:
Detecting and parsing architecture at city scale from range data. CVPR 2010: 398-405 - [c39]Benjamin Sapp, Chris Jordan, Ben Taskar:
Adaptive pose priors for pictorial structures. CVPR 2010: 422-429 - [c38]Alexander Toshev, Ben Taskar, Kostas Daniilidis:
Object detection via boundary structure segmentation. CVPR 2010: 950-957 - [c37]Timothée Cour, Benjamin Sapp, Akash Nagle, Ben Taskar:
Talking pictures: Temporal grouping and dialog-supervised person recognition. CVPR 2010: 1014-1021 - [c36]Benjamin Sapp, Alexander Toshev, Ben Taskar:
Cascaded Models for Articulated Pose Estimation. ECCV (2) 2010: 406-420 - [c35]Alex Kulesza, Ben Taskar:
Structured Determinantal Point Processes. NIPS 2010: 1171-1179 - [c34]Umar Syed, Ben Taskar:
Semi-Supervised Learning with Adversarially Missing Label Information. NIPS 2010: 2244-2252 - [c33]David J. Weiss, Benjamin Sapp, Ben Taskar:
Sidestepping Intractable Inference with Structured Ensemble Cascades. NIPS 2010: 2415-2423 - [c32]David J. Weiss, Benjamin Taskar:
Structured Prediction Cascades. AISTATS 2010: 916-923 - 2009
- [c31]Kuzman Ganchev, Jennifer Gillenwater, Ben Taskar:
Dependency Grammar Induction via Bitext Projection Constraints. ACL/IJCNLP 2009: 369-377 - [c30]Timothée Cour, Benjamin Sapp, Chris Jordan, Benjamin Taskar:
Learning from ambiguously labeled images. CVPR 2009: 919-926 - [c29]Nematollah Batmanghelich, Ben Taskar, Christos Davatzikos:
A General and Unifying Framework for Feature Construction, in Image-Based Pattern Classification. IPMI 2009: 423-434 - [c28]João Graça, Kuzman Ganchev, Ben Taskar, Fernando C. N. Pereira:
Posterior vs Parameter Sparsity in Latent Variable Models. NIPS 2009: 664-672 - [c27]Yuanqing Lin, Shenghuo Zhu, Daniel D. Lee, Ben Taskar:
Learning Sparse Markov Network Structure via Ensemble-of-Trees Models. AISTATS 2009: 360-367 - 2008
- [c26]Kuzman Ganchev, João Graça, Ben Taskar:
Better Alignments = Better Translations? ACL 2008: 986-993 - [c25]Timothée Cour, Chris Jordan, Eleni Miltsakaki, Ben Taskar:
Movie/Script: Alignment and Parsing of Video and Text Transcription. ECCV (4) 2008: 158-171 - [c24]Paul Vernaza, Ben Taskar, Daniel D. Lee:
Online, self-supervised terrain classification via discriminatively trained submodular Markov random fields. ICRA 2008: 2750-2757 - [c23]Kuzman Ganchev, João Graça, John Blitzer, Ben Taskar:
Multi-View Learning over Structured and Non-Identical Outputs. UAI 2008: 88-96 - [c22]Kuzman Ganchev, João Graça, John Blitzer, Ben Taskar:
Multi-View Learning over Structured and Non-Identical Outputs. UAI 2008: 204-211 - 2007
- [c21]Percy Liang, Michael I. Jordan, Benjamin Taskar:
A permutation-augmented sampler for DP mixture models. ICML 2007: 545-552 - [c20]João Graça, Kuzman Ganchev, Ben Taskar:
Expectation Maximization and Posterior Constraints. NIPS 2007: 569-576 - [c19]David S. Rosenberg, Dan Klein, Ben Taskar:
Mixture-of-Parents Maximum Entropy Markov Models. UAI 2007: 318-325 - 2006
- [c18]Percy Liang, Alexandre Bouchard-Côté, Dan Klein, Benjamin Taskar:
An End-to-End Discriminative Approach to Machine Translation. ACL 2006 - [c17]Simon Lacoste-Julien, Benjamin Taskar, Dan Klein, Michael I. Jordan:
Word Alignment via Quadratic Assignment. HLT-NAACL 2006 - [c16]Percy Liang, Benjamin Taskar, Dan Klein:
Alignment by Agreement. HLT-NAACL 2006 - 2005
- [c15]Dragomir Anguelov, Benjamin Taskar, Vassil Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz, Andrew Y. Ng:
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data. CVPR (2) 2005: 169-176 - [c14]Benjamin Taskar, Vassil Chatalbashev, Daphne Koller, Carlos Guestrin:
Learning structured prediction models: a large margin approach. ICML 2005: 896-903 - [c13]Benjamin Taskar, Simon Lacoste-Julien, Dan Klein:
A Discriminative Matching Approach to Word Alignment. HLT/EMNLP 2005: 73-80 - [c12]Benjamin Taskar, Simon Lacoste-Julien, Michael I. Jordan:
Structured Prediction via the Extragradient Method. NIPS 2005: 1345-1352 - 2004
- [c11]Ben Taskar, Dan Klein, Michael Collins, Daphne Koller, Christopher D. Manning:
Max-Margin Parsing. EMNLP 2004: 1-8 - [c10]Benjamin Taskar, Vassil Chatalbashev, Daphne Koller:
Learning associative Markov networks. ICML 2004 - [c9]Peter L. Bartlett, Michael Collins, Benjamin Taskar, David A. McAllester:
Exponentiated Gradient Algorithms for Large-margin Structured Classification. NIPS 2004: 113-120 - 2003
- [c8]Benjamin Taskar, Ming Fai Wong, Daphne Koller:
Learning on the Test Data: Leveraging Unseen Features. ICML 2003: 744-751 - [c7]Benjamin Taskar, Carlos Guestrin, Daphne Koller:
Max-Margin Markov Networks. NIPS 2003: 25-32 - [c6]Benjamin Taskar, Ming Fai Wong, Pieter Abbeel, Daphne Koller:
Link Prediction in Relational Data. NIPS 2003: 659-666 - 2002
- [c5]Benjamin Taskar, Pieter Abbeel, Daphne Koller:
Discriminative Probabilistic Models for Relational Data. UAI 2002: 485-492 - 2001
- [c4]Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar:
Learning Probabilistic Models of Relational Structure. ICML 2001: 170-177 - [c3]Benjamin Taskar, Eran Segal, Daphne Koller:
Probabilistic Classification and Clustering in Relational Data. IJCAI 2001: 870-878 - [c2]Eran Segal, Benjamin Taskar, Audrey P. Gasch, Nir Friedman, Daphne Koller:
Rich probabilistic models for gene expression. ISMB (Supplement of Bioinformatics) 2001: 243-252 - [c1]Lise Getoor, Benjamin Taskar, Daphne Koller:
Selectivity Estimation using Probabilistic Models. SIGMOD Conference 2001: 461-472
Informal and Other Publications
- 2014
- [i10]João Graça, Kuzman Ganchev, Luísa Coheur, Fernando Pereira, Ben Taskar:
Controlling Complexity in Part-of-Speech Induction. CoRR abs/1401.6131 (2014) - [i9]Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams, Ben Taskar:
Learning the Parameters of Determinantal Point Process Kernels. CoRR abs/1402.4862 (2014) - [i8]Jennifer Gillenwater, Alex Kulesza, Emily B. Fox, Ben Taskar:
Expectation-Maximization for Learning Determinantal Point Processes. CoRR abs/1411.1088 (2014) - 2013
- [i7]Ben Taskar, Pieter Abbeel, Daphne Koller:
Discriminative Probabilistic Models for Relational Data. CoRR abs/1301.0604 (2013) - [i6]Raja Hafiz Affandi, Emily B. Fox, Ben Taskar:
Approximate Inference in Continuous Determinantal Point Processes. CoRR abs/1311.2971 (2013) - 2012
- [i5]Alex Kulesza, Ben Taskar:
Learning Determinantal Point Processes. CoRR abs/1202.3738 (2012) - [i4]Kuzman Ganchev, João Graça, John Blitzer, Ben Taskar:
Multi-View Learning over Structured and Non-Identical Outputs. CoRR abs/1206.3256 (2012) - [i3]David S. Rosenberg, Dan Klein, Ben Taskar:
Mixture-of-Parents Maximum Entropy Markov Models. CoRR abs/1206.5261 (2012) - [i2]Alex Kulesza, Ben Taskar:
Determinantal point processes for machine learning. CoRR abs/1207.6083 (2012) - [i1]David J. Weiss, Benjamin Sapp, Ben Taskar:
Structured Prediction Cascades. CoRR abs/1208.3279 (2012)
Coauthor Index
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