Learning Probabilistic Models of Relational Structure. - Lise Getoor; Nir Friedman; Daphne Koller; Benjamin Taskar (ICML, 2001)

Probabilistic Classification and Clustering in Relational Data. - Benjamin Taskar; Eran Segal; Daphne Koller (IJCAI, 2001)

Rich probabilistic models for gene expression. - Eran Segal; Benjamin Taskar; Audrey P. Gasch; Nir Friedman; Daphne Koller (ISMB (Supplement of Bioinformatics), 2001)

Selectivity Estimation using Probabilistic Models. - Lise Getoor; Benjamin Taskar; Daphne Koller (SIGMOD Conference, 2001)

Discriminative Probabilistic Models for Relational Data. - Benjamin Taskar; Pieter Abbeel; Daphne Koller (UAI, 2002)

Learning Probabilistic Models of Link Structure. - Lise Getoor; Nir Friedman; Daphne Koller; Benjamin Taskar (J. Mach. Learn. Res., 2002)

Learning on the Test Data: Leveraging Unseen Features. - Benjamin Taskar; Ming Fai Wong; Daphne Koller (ICML, 2003)

Max-Margin Markov Networks. - Benjamin Taskar; Carlos Guestrin; Daphne Koller (NIPS, 2003)

Link Prediction in Relational Data. - Benjamin Taskar; Ming Fai Wong; Pieter Abbeel; Daphne Koller (NIPS, 2003)

Max-Margin Parsing. - Ben Taskar; Dan Klein 001; Michael Collins 001; Daphne Koller; Christopher D. Manning (EMNLP, 2004)

Learning associative Markov networks. - Benjamin Taskar; Vassil Chatalbashev; Daphne Koller (ICML, 2004)

Exponentiated Gradient Algorithms for Large-margin Structured Classification. - Peter L. Bartlett; Michael Collins 001; Benjamin Taskar; David A. McAllester (NIPS, 2004)

Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data. - Dragomir Anguelov; Benjamin Taskar; Vassil Chatalbashev; Daphne Koller; Dinkar Gupta; Geremy Heitz; Andrew Y. Ng (CVPR (2), 2005)

Learning structured prediction models: a large margin approach. - Benjamin Taskar; Vassil Chatalbashev; Daphne Koller; Carlos Guestrin (ICML, 2005)

A Discriminative Matching Approach to Word Alignment. - Benjamin Taskar; Simon Lacoste-Julien; Dan Klein 001 (HLT/EMNLP, 2005)

Structured Prediction via the Extragradient Method. - Benjamin Taskar; Simon Lacoste-Julien; Michael I. Jordan (NIPS, 2005)

Learning structured prediction models : a large margin approach. - Ben Taskar (2005)

An End-to-End Discriminative Approach to Machine Translation. - Percy Liang; Alexandre Bouchard-Côté; Dan Klein 001; Benjamin Taskar (ACL, 2006)

Word Alignment via Quadratic Assignment. - Simon Lacoste-Julien; Benjamin Taskar; Dan Klein 001; Michael I. Jordan (HLT-NAACL, 2006)

Alignment by Agreement. - Percy Liang; Benjamin Taskar; Dan Klein 001 (HLT-NAACL, 2006)

Structured Prediction, Dual Extragradient and Bregman Projections. - Benjamin Taskar; Simon Lacoste-Julien; Michael I. Jordan (J. Mach. Learn. Res., 2006)

A permutation-augmented sampler for DP mixture models. - Percy Liang; Michael I. Jordan; Benjamin Taskar (ICML, 2007)

Expectation Maximization and Posterior Constraints. - João Graça; Kuzman Ganchev; Ben Taskar (NIPS, 2007)

Mixture-of-Parents Maximum Entropy Markov Models. - David S. Rosenberg; Dan Klein 001; Ben Taskar (UAI, 2007)

Better Alignments = Better Translations? - Kuzman Ganchev; João Graça; Ben Taskar (ACL, 2008)

Movie/Script: Alignment and Parsing of Video and Text Transcription. - Timothée Cour; Chris Jordan; Eleni Miltsakaki; Ben Taskar (ECCV (4), 2008)

Online, self-supervised terrain classification via discriminatively trained submodular Markov random fields. - Paul Vernaza; Ben Taskar; Daniel D. Lee (ICRA, 2008)

Multi-View Learning over Structured and Non-Identical Outputs. - Kuzman Ganchev; João Graça; John Blitzer; Ben Taskar (UAI, 2008)

Dependency Grammar Induction via Bitext Projection Constraints. - Kuzman Ganchev; Jennifer Gillenwater; Ben Taskar (ACL/IJCNLP, 2009)

Learning from ambiguously labeled images. - Timothée Cour; Benjamin Sapp; Chris Jordan; Benjamin Taskar (CVPR, 2009)

A General and Unifying Framework for Feature Construction, in Image-Based Pattern Classification. - Nematollah Batmanghelich; Ben Taskar; Christos Davatzikos (IPMI, 2009)

Posterior vs Parameter Sparsity in Latent Variable Models. - João Graça; Kuzman Ganchev; Ben Taskar; Fernando C. N. Pereira (NIPS, 2009)

Learning Sparse Markov Network Structure via Ensemble-of-Trees Models. - Yuanqing Lin; Shenghuo Zhu; Daniel D. Lee; Ben Taskar (AISTATS, 2009)

PostCAT - Posterior Constrained Alignment Toolkit. - João Graça; Kuzman Ganchev; Ben Taskar (Prague Bull. Math. Linguistics, 2009)

Sparsity in Dependency Grammar Induction. - Jennifer Gillenwater; Kuzman Ganchev; João Graça; Fernando Pereira 003; Ben Taskar (ACL (2), 2010)

Application of trace-norm and low-rank matrix decomposition for computational anatomy. - Nematollah Batmanghelich; Ali Gooya; Stathis Kanterakis; Ben Taskar; Christos Davatzikos (CVPR Workshops, 2010)

Talking pictures: Temporal grouping and dialog-supervised person recognition. - Timothée Cour; Benjamin Sapp; Akash Nagle; Ben Taskar (CVPR, 2010)

Adaptive pose priors for pictorial structures. - Benjamin Sapp; Chris Jordan; Ben Taskar (CVPR, 2010)

Detecting and parsing architecture at city scale from range data. - Alexander Toshev; Philippos Mordohai; Ben Taskar (CVPR, 2010)

Object detection via boundary structure segmentation. - Alexander Toshev; Ben Taskar; Kostas Daniilidis (CVPR, 2010)

Cascaded Models for Articulated Pose Estimation. - Benjamin Sapp; Alexander Toshev; Ben Taskar (ECCV (2), 2010)

Structured Determinantal Point Processes. - Alex Kulesza; Ben Taskar (NIPS, 2010)

Semi-Supervised Learning with Adversarially Missing Label Information. - Umar Syed; Ben Taskar (NIPS, 2010)

Sidestepping Intractable Inference with Structured Ensemble Cascades. - David J. Weiss; Benjamin Sapp; Ben Taskar (NIPS, 2010)

Learning Tractable Word Alignment Models with Complex Constraints. - João Graça; Kuzman Ganchev; Ben Taskar (Comput. Linguistics, 2010)

Posterior Regularization for Structured Latent Variable Models. - Kuzman Ganchev; João Graça; Jennifer Gillenwater; Ben Taskar (J. Mach. Learn. Res., 2010)

Structured Prediction Cascades. - David J. Weiss; Benjamin Taskar (AISTATS, 2010)

Joint covariate selection and joint subspace selection for multiple classification problems. - Guillaume Obozinski; Ben Taskar; Michael I. Jordan (Stat. Comput., 2010)

Parsing human motion with stretchable models. - Benjamin Sapp; David J. Weiss; Ben Taskar (CVPR, 2011)

k-DPPs: Fixed-Size Determinantal Point Processes. - Alex Kulesza; Ben Taskar (ICML, 2011)

Disease classification and prediction via semi-supervised dimensionality reduction. - Kayhan N. Batmanghelich; Dong Hye Ye; Kilian M. Pohl; Ben Taskar; Christos Davatzikos (ISBI, 2011)

Regularized Tensor Factorization for Multi-Modality Medical Image Classification. - Nematollah Batmanghelich; Aoyan Dong; Ben Taskar; Christos Davatzikos (MICCAI (3), 2011)

Learning Determinantal Point Processes. - Alex Kulesza; Ben Taskar (UAI, 2011)

Controlling Complexity in Part-of-Speech Induction. - João Graça; Kuzman Ganchev; Luísa Coheur; Fernando Pereira 003; Benjamin Taskar (J. Artif. Intell. Res., 2011)

Learning from Partial Labels. - Timothée Cour; Benjamin Sapp; Ben Taskar (J. Mach. Learn. Res., 2011)

Posterior Sparsity in Unsupervised Dependency Parsing. - Jennifer Gillenwater; Kuzman Ganchev; João Graça; Fernando Pereira 003; Ben Taskar (J. Mach. Learn. Res., 2011)

Discovering Diverse and Salient Threads in Document Collections. - Jennifer Gillenwater; Alex Kulesza; Ben Taskar (EMNLP-CoNLL, 2012)

Wiki-ly Supervised Part-of-Speech Tagging. - Shen Li; João Graça; Ben Taskar (EMNLP-CoNLL, 2012)

Near-Optimal MAP Inference for Determinantal Point Processes. - Jennifer Gillenwater; Alex Kulesza; Ben Taskar (NIPS, 2012)

Structured Prediction Cascades - David J. Weiss; Benjamin Sapp; Ben Taskar (CoRR, 2012)

Determinantal Point Processes for Machine Learning. - Alex Kulesza; Ben Taskar (Found. Trends Mach. Learn., 2012)

Shape-Based Object Detection via Boundary Structure Segmentation. - Alexander Toshev; Ben Taskar; Kostas Daniilidis (Int. J. Comput. Vis., 2012)

Generative-Discriminative Basis Learning for Medical Imaging. - Nematollah Batmanghelich; Ben Taskar; Christos Davatzikos (IEEE Trans. Medical Imaging, 2012)

Nystrom Approximation for Large-Scale Determinantal Processes. - Raja Hafiz Affandi; Alex Kulesza; Emily B. Fox; Ben Taskar (AISTATS, 2013)

Graph-Based Posterior Regularization for Semi-Supervised Structured Prediction. - Luheng He; Jennifer Gillenwater; Ben Taskar (CoNLL, 2013)

MODEC: Multimodal Decomposable Models for Human Pose Estimation. - Benjamin Sapp; Ben Taskar (CVPR, 2013)

SCALPEL: Segmentation Cascades with Localized Priors and Efficient Learning. - David J. Weiss; Ben Taskar (CVPR, 2013)

The Tangent Earth Mover's Distance. - Ofir Pele; Ben Taskar (GSI, 2013)

Dynamic Structured Model Selection. - David J. Weiss; Benjamin Sapp; Ben Taskar (ICCV, 2013)

Collective Stability in Structured Prediction: Generalization from One Example. - Ben London 001; Bert Huang; Ben Taskar; Lise Getoor (ICML (3), 2013)

The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification. - Ofir Pele; Ben Taskar; Amir Globerson; Michael Werman (ICML (1), 2013)

Approximate Inference in Continuous Determinantal Processes. - Raja Hafiz Affandi; Emily B. Fox; Ben Taskar (NIPS, 2013)

Learning Adaptive Value of Information for Structured Prediction. - David J. Weiss; Ben Taskar (NIPS, 2013)

Approximate Inference in Continuous Determinantal Point Processes. - Raja Hafiz Affandi; Emily B. Fox; Ben Taskar (CoRR, 2013)

PAC-Bayesian Collective Stability. - Ben London 001; Bert Huang; Ben Taskar; Lise Getoor (AISTATS, 2014)

Non-intrusive tongue machine interface. - Qiao Zhang 001; Shyamnath Gollakota; Ben Taskar; Raj P. N. Rao (CHI, 2014)

Understanding Objects in Detail with Fine-Grained Attributes. - 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; et al. (CVPR, 2014)

Salient Montages from Unconstrained Videos. - Min Sun 001; Ali Farhadi; Ben Taskar; Steven M. Seitz (ECCV (7), 2014)

Learning the Parameters of Determinantal Point Process Kernels. - Raja Hafiz Affandi; Emily B. Fox; Ryan P. Adams; Benjamin Taskar (ICML, 2014)

Expectation-Maximization for Learning Determinantal Point Processes. - Jennifer Gillenwater; Alex Kulesza; Emily B. Fox; Benjamin Taskar (NIPS, 2014)

The Swarm at the Edge of the Cloud. - 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; et al. (IEEE Des. Test, 2014)

Efficient Second-Order Gradient Boosting for Conditional Random Fields. - Tianqi Chen 001; Sameer Singh 001; Ben Taskar; Carlos Guestrin (AISTATS, 2015)

Summarizing Unconstrained Videos Using Salient Montages. - Min Sun 001; Ali Farhadi; Ben Taskar; Steven M. Seitz (IEEE Trans. Pattern Anal. Mach. Intell., 2017)