World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
64
Citations
20665
World Ranking
2553
National Ranking
1276

Research.com Recognitions

  • 2010 - Fellow of Alfred P. Sloan Foundation

Overview

Ben Taskar was affiliated with the University of Washington in the United States. Their academic career involved research in domains that are not explicitly detailed in the provided data.

Taskar was recognized with the title of Fellow of the Alfred P. Sloan Foundation in 2010. This award is typically granted to early-career scientists showing potential in their respective fields, reflecting a measure of distinction during their professional activity.

There are no records available regarding Ben Taskar's recent scholarly papers, frequent co-authors, or typical publication venues. Similarly, there are no specified books published or detailed research subfields and main topics associated with them. This absence suggests that publicly recorded bibliometric and collaborative patterns are limited or were not provided.

Best Publications

  • Introduction to statistical relational learning

    Lise Getoor;Ben Taskar

  • Max-Margin Markov Networks

    Ben Taskar;Carlos Guestrin;Daphne Koller

  • Determinantal Point Processes for Machine Learning

    Alex Kulesza;Ben Taskar

  • Discriminative probabilistic models for relational data

    Ben Taskar;Pieter Abbeel;Daphne Koller

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

    Lise Getoor;Ben Taskar

  • Learning structured prediction models: a large margin approach

    Ben Taskar;Vassil Chatalbashev;Daphne Koller;Carlos Guestrin

  • Link Prediction in Relational Data

    Ben Taskar;Ming-fai Wong;Pieter Abbeel;Daphne Koller

  • Joint covariate selection and joint subspace selection for multiple classification problems

    Guillaume Obozinski;Ben Taskar;Michael I. Jordan

  • Alignment by Agreement

    Percy Liang;Ben Taskar;Dan Klein

  • Posterior Regularization for Structured Latent Variable Models

    Kuzman Ganchev;João Graça;Jennifer Gillenwater;Ben Taskar

  • MODEC: Multimodal Decomposable Models for Human Pose Estimation

    Ben Sapp;Ben Taskar

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

    D. Anguelov;B. Taskarf;V. Chatalbashev;D. Koller

  • Rich probabilistic models for gene expression.

    Eran Segal;Benjamin Taskar;Audrey P. Gasch;Nir Friedman

  • Probabilistic classification and clustering in relational data

    Ben Taskar;Eran Segal;Daphne Koller

  • Learning from Partial Labels

    Timothee Cour;Ben Sapp;Ben Taskar

  • An End-to-End Discriminative Approach to Machine Translation

    Percy Liang;Alexandre Bouchard-Côté;Dan Klein;Ben Taskar

  • Selectivity estimation using probabilistic models

    Lise Getoor;Benjamin Taskar;Daphne Koller

  • Cascaded models for articulated pose estimation

    Benjamin Sapp;Alexander Toshev;Ben Taskar

  • Method and apparatus for learning probabilistic relational models having attribute and link uncertainty and for performing selectivity estimation using probabilistic relational models

    Daphne Koller;Lise Getoor;Avi Pfeffer;Nir Friedman

  • Max-Margin Parsing

    Ben Taskar;Dan Klein;Michael Collins;Daphne Koller

  • An Introduction to Conditional Random Fields for Relational Learning

    Lise Getoor;Ben Taskar

Frequent Co-Authors

Lise Getoor
Lise Getoor University of California, Santa Cruz
Thomas Hofmann
Thomas Hofmann ETH Zurich
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Alexander J. Smola
Alexander J. Smola Amazon (United States)
S. V. N. Vishwanathan
S. V. N. Vishwanathan Purdue University West Lafayette
Daphne Koller
Daphne Koller insitro Inc.
Emily B. Fox
Emily B. Fox Stanford University
Fernando Pereira
Fernando Pereira Google (United States)
Daniel Klein
Daniel Klein University of California, Berkeley
Christos Davatzikos
Christos Davatzikos University of Pennsylvania

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