B. Taskar

发表

Multi-task feature selection

Michael I. Jordan, G. Obozinski, B. Taskar, 2006 .

Max-Margin Markov Networks

Ben Taskar, Carlos Guestrin, Daphne Koller, 2003, NIPS.

Predicting Structured Data (Neural Information Processing)

Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola, 2007 .

Salient Montages from Unconstrained Videos

Ali Farhadi, Ben Taskar, Min Sun, 2014, ECCV.

Learning from ambiguously labeled images

B. Taskar, Timothée Cour, Benjamin Sapp, 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

Learning structured prediction models: a large margin approach

Ben Taskar, Carlos Guestrin, Daphne Koller, 2005, ICML.

Alignment by Agreement

Ben Taskar, Dan Klein, Percy Liang, 2006, NAACL.

An End-to-End Discriminative Approach to Machine Translation

Ben Taskar, Dan Klein, Percy Liang, 2006, ACL.

Structured Prediction via the Extragradient Method

Ben Taskar, Michael I. Jordan, Simon Lacoste-Julien, 2005, NIPS.

MODEC: Multimodal Decomposable Models for Human Pose Estimation

Ben Taskar, Benjamin Sapp, B. Taskar, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Understanding Objects in Detail with Fine-Grained Attributes

Iasonas Kokkinos, Subhransu Maji, Ben Taskar, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Probabilistic Classification and Clustering in Relational Data

Ben Taskar, Daphne Koller, Eran Segal, 2001, IJCAI.

Discriminative learning of Markov random fields for segmentation of 3D scan data

Ben Taskar, Dragomir Anguelov, Andrew Y. Ng, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

Probabilistic Models of Text and Link Structure for Hypertext Classification

Ben Taskar, Lise Getoor, Daphne Koller, 2001 .

Max-Margin Parsing

Ben Taskar, Dan Klein, Christopher D. Manning, 2004, EMNLP.

Introduction to statistical relational learning

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Discriminative Probabilistic Models for Relational Data pdf

Ben Taskar, Pieter Abbeel, Daphne Koller, 2002, UAI.

An Introduction to Conditional Random Fields for Relational Learning

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Word Alignment via Quadratic Assignment

Ben Taskar, Dan Klein, Michael I. Jordan, 2006, NAACL.

Generalization Bounds and Consistency for Structured Labeling

Gökhan BakIr, Thomas Hofmann, Bernhard Schölkopf, 2007 .

Multi-Label Learning with Posterior Regularization

Xi Victoria Lin, Luke Zettlemoyer, B. Taskar, 2014 .

Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Shape-Based Object Detection via Boundary Structure Segmentation

Ben Taskar, Kostas Daniilidis, Alexander Toshev, 2012, International Journal of Computer Vision.

Learning Probabilistic Models of Relational Structure

Ben Taskar, Lise Getoor, Nir Friedman, 2001, ICML.

Expectation Maximization and Posterior Constraints

Ben Taskar, João Graça, Kuzman Ganchev, 2007, NIPS.

1 Global Inference for Entity and Relation Identification via a Linear Programming Formulation

L. Getoor, B. Taskar, Dan Roth, 2007 .

Sidestepping Intractable Inference with Structured Ensemble Cascades

Ben Taskar, Benjamin Sapp, David J. Weiss, 2010, NIPS.

Joint covariate selection and joint subspace selection for multiple classification problems

Ben Taskar, Michael I. Jordan, Guillaume Obozinski, 2010, Stat. Comput..

Exponentiated Gradient Algorithms for Large-margin Structured Classification

Ben Taskar, Peter L. Bartlett, Michael Collins, 2004, NIPS.

Structured Prediction, Dual Extragradient and Bregman Projections

Ben Taskar, Michael I. Jordan, Simon Lacoste-Julien, 2006, J. Mach. Learn. Res..

Object detection via boundary structure segmentation

Ben Taskar, Kostas Daniilidis, Alexander Toshev, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Rich probabilistic models for gene expression

Ben Taskar, Nir Friedman, Daphne Koller, 2001, ISMB.

A permutation-augmented sampler for DP mixture models

Ben Taskar, Michael I. Jordan, Percy Liang, 2007, ICML '07.

Detecting and parsing architecture at city scale from range data

Ben Taskar, Philippos Mordohai, Alexander Toshev, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

The swarm at the edge of the cloud - A new perspective on wireless

Edward A. Lee, Alberto L. Sangiovanni-Vincentelli, David Blaauw, 2011, 2011 Symposium on VLSI Circuits - Digest of Technical Papers.

Determinantal Point Processes for Machine Learning

Ben Taskar, Alex Kulesza, B. Taskar, 2012, Found. Trends Mach. Learn..

Near-Optimal MAP Inference for Determinantal Point Processes

Ben Taskar, Alex Kulesza, Jennifer Gillenwater, 2012, NIPS.

2 Graphical Models in a Nutshell

D. Koller, N. Friedman, L. Getoor, 2008 .

Large margin methods for structured classification : Exponentiated gradient algorithms and PAC-Bayesian generalization bounds

Ben Taskar, Peter L. Bartlett, Michael Collins, 2004 .

Learning associative Markov networks

Ben Taskar, Daphne Koller, Vassil Chatalbashev, 2004, ICML.

Selectivity estimation using probabilistic models

Ben Taskar, Lise Getoor, Daphne Koller, 2001, SIGMOD '01.

Graph-Based Posterior Regularization for Semi-Supervised Structured Prediction

Ben Taskar, Luheng He, Jennifer Gillenwater, 2013, CoNLL.

Probabilistic Relational Models

Ben Taskar, Lise Getoor, L. Getoor, 2014, Encyclopedia of Social Network Analysis and Mining.

Label and Link Prediction in Relational Data

P. Abbeel, D. Koller, B. Taskar, 2003 .

Talking pictures: Temporal grouping and dialog-supervised person recognition

Ben Taskar, Benjamin Sapp, Timothée Cour, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Learning on the Test Data: Leveraging Unseen Features

Ben Taskar, Daphne Koller, Ming Fai Wong, 2003, ICML.

6 Relational Markov Networks

P. Abbeel, D. Koller, B. Taskar, 2007 .

Learning Tractable Word Alignment Models with Non-Markovian Constraints

B. Taskar, K. Ganchev, João Graça, 2009 .

Posterior Regularization for Structured Latent Variable Models

Ben Taskar, João Graça, Kuzman Ganchev, 2010, J. Mach. Learn. Res..

Logic-based Formalisms for Statistical Relational Learning

L. Getoor, B. Taskar, 2007 .

LARGE MARGIN DISCRIMINATIVE LEARNING METHODS FOR ACOUSTIC MODELING

Kilian Q. Weinberger, L. Saul, S. Roweis, 2006 .

PAC-Bayesian Collective Stability Supplemental Material

L. Getoor, B. Taskar, Ben London, 2014 .

Structured Prediction Based on Discriminative Models

Gökhan BakIr, Thomas Hofmann, Bernhard Schölkopf, 2007 .

Discriminative Learning of Prediction Suffix Trees with the Perceptron Algorithm

Gökhan BakIr, Thomas Hofmann, Bernhard Schölkopf, 2007 .

Probabilistic Entity-Relationship Models, PRMs, and Plate Models

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Towards a Detailed Understanding of Objects and Scenes in Natural Images

Iasonas Kokkinos, Subhransu Maji, Ben Taskar, 2012 .

The Design and Implementatin of IBAL: A General-Purpose Probabilistic Language

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Shape-based Object Detection via Boundary Structure

Ben Taskar, Kostas Daniilidis, Alexander Toshev, 2011 .

BLOG: Probabilistic Models with Unknown Objects

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Inductive Logic Programming in a Nutshell

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Expectation Maximization, Posterior Constraints, and Statistical Alignment

Ben Taskar, B. Taskar, 2007, NIPS 2007.

Bayesian Logic Programming: Theory and Tool

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Lifted First-Order Probabilistic Inference

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Posterior Sparsity in Dependency Grammar Induction

Ben Taskar, Kuzman Ganchev, Jennifer Gillenwater, 2011 .

Learning a New View of a Database: With an Application in Mammography

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Graphical Models in a Nutshell

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Learning from Partial Labels

Ben Taskar, Benjamin Sapp, Timothée Cour, 2011, J. Mach. Learn. Res..

Application of trace-norm and low-rank matrix decomposition for computational anatomy

Ben Taskar, Christos Davatzikos, Ali Gooya, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.

PAC-Bayesian Collective Stability

Ben Taskar, Lise Getoor, Bert Huang, 2014, AISTATS.

Collective Stability in Structured Prediction: Generalization from One Example

Ben Taskar, Lise Getoor, Bert Huang, 2013, ICML.

Collective Stability in Structured Prediction: Appendix

L. Getoor, B. Taskar, Ben London, 2008 .

Approximate Inference in Continuous Determinantal Processes

Ben Taskar, Emily B. Fox, Raja Hafiz Affandi, 2013, NIPS.

Link Prediction in Relational Data

Ben Taskar, Pieter Abbeel, Daphne Koller, 2003, NIPS.

The Tangent Earth Mover's Distance

Ben Taskar, Ofir Pele, B. Taskar, 2013, GSI.

Generative-Discriminative Basis Learning for Medical Imaging

Ben Taskar, Christos Davatzikos, Nematollah Batmanghelich, 2012, IEEE Transactions on Medical Imaging.

Disease classification and prediction via semi-supervised dimensionality reduction

Ben Taskar, Christos Davatzikos, Kilian M. Pohl, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

An efficient algorithm for the symmetric principal minor assignment problem

Ben Taskar, Alex Kulesza, Justin K. Rising, 2015 .

Structured Prediction Cascades

Ben Taskar, David J. Weiss, B. Taskar, 2010, AISTATS.

Multi-View Learning over Structured and Non-Identical Outputs pdf

Ben Taskar, John Blitzer, João Graça, 2008, UAI.

Learning Determinantal Point Processes

Ben Taskar, Alex Kulesza, B. Taskar, 2011, UAI.

k-DPPs: Fixed-Size Determinantal Point Processes

Ben Taskar, Alex Kulesza, B. Taskar, 2011, ICML.

Relational Markov Networks

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Cascaded Models for Articulated Pose Estimation

Ben Taskar, Benjamin Sapp, Alexander Toshev, 2010, ECCV.

Non-intrusive tongue machine interface

Ben Taskar, Rajesh P. N. Rao, Qiao Zhang, 2014, CHI.

Learning Probabilistic Models of Link Structure

Ben Taskar, Lise Getoor, Nir Friedman, 2003, J. Mach. Learn. Res..

Learning the Parameters of Determinantal Point Process Kernels

Ben Taskar, Ryan P. Adams, Emily B. Fox, 2014, ICML.

Expectation-Maximization for Learning Determinantal Point Processes

Ben Taskar, Alex Kulesza, Emily B. Fox, 2014, NIPS.

Markov Logic: A Unifying Framework for Statistical Relational Learning

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Movie/Script: Alignment and Parsing of Video and Text Transcription

Ben Taskar, Christopher T. Jordan, Timothée Cour, 2008, ECCV.

Recognizing Violence in Movies CIS 400 / 401 Project Final Report

B. Taskar, Lei Kang kanglei, 2011 .

The Swarm at the Edge of the Cloud

Anthony Rowe, Edward A. Lee, David Blaauw, 2015, IEEE Design & Test.

Parsing human motion with stretchable models

Ben Taskar, Benjamin Sapp, David J. Weiss, 2011, CVPR 2011.

A Discriminative Matching Approach to Word Alignment

Ben Taskar, Dan Klein, Simon Lacoste-Julien, 2005, HLT.

Summarizing Unconstrained Videos Using Salient Montages

Ali Farhadi, Ben Taskar, Min Sun, 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Adaptive pose priors for pictorial structures

Ben Taskar, Benjamin Sapp, Christopher T. Jordan, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Learning Adaptive Value of Information for Structured Prediction

Ben Taskar, David J. Weiss, B. Taskar, 2013, NIPS.

The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification

Ben Taskar, Michael Werman, Amir Globerson, 2013, ICML.

Stuctured Predictions Cascades

Ben Taskar, David J. Weiss, B. Taskar, 2010 .

Wiki-ly Supervised Part-of-Speech Tagging

Ben Taskar, João Graça, Shen Li, 2012, EMNLP.

Learning Tractable Word Alignment Models with Complex Constraints

Ben Taskar, João Graça, Kuzman Ganchev, 2010, CL.

Predicting Structured Data

Gökhan BakIr, Sundar Vishwanathan, Bernhard Schölkopf, 2008 .

Discovering Diverse and Salient Threads in Document Collections

Ben Taskar, Alex Kulesza, Jennifer Gillenwater, 2012, EMNLP.

Large-Scale Modeling of Diverse Paths using Structured k-DPPs

B. Taskar, Alex Kulesza, Jennifer Gillenwater, 2012 .

Efficient Algorithms for Max-Margin Structured Classification

Gökhan BakIr, Thomas Hofmann, Bernhard Schölkopf, 2007 .

Structured Determinantal Point Processes

Ben Taskar, Alex Kulesza, B. Taskar, 2010, NIPS.

SCALPEL: Segmentation Cascades with Localized Priors and Efficient Learning

Ben Taskar, David J. Weiss, B. Taskar, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Feature Generation and Selection in Multi-Relational Statistical Learning

Ben Taskar, Lise Getoor, L. Getoor, 2007 .

Online, self-supervised terrain classification via discriminatively trained submodular Markov random fields

Ben Taskar, Daniel D. Lee, Paul Vernaza, 2008, 2008 IEEE International Conference on Robotics and Automation.

A General and Unifying Framework for Feature Construction, in Image-Based Pattern Classification

Ben Taskar, Christos Davatzikos, Nematollah Batmanghelich, 2009, IPMI.

Learning structured prediction models: a large margin approach

D. Koller, Carlos Guestrin, B. Taskar, 2005, ICML.

Learning Probabilistic Relational Models with Structural Uncertainty

Lise Getoor, Nir Friedman, Daphne Koller, 2000 .

Multi-Label Learning with Posterior Regularization

Xi Victoria Lin, Luke Zettlemoyer, B. Taskar, 2014 .

Introduction to statistical relational learning

L. Getoor, B. Taskar, 2007 .