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David Maxwell Chickering

David Maxwell Chickering

D-Index & Metrics

Computer Science

D-Index
58
Citations
21496
World Ranking
3546
National Ranking
1706

Overview

David Maxwell Chickering is affiliated with Microsoft in the United States. Their career is primarily based in the United States, where they engage in research activities connected to this leading technology organization.

Information on their recent papers, including titles, year of publication, and venues, is not available. Similarly, no data about frequent co-authors, publication venues, or book publications has been documented.

Their research areas, including main fields of study, subfields, and primary topics, are not listed in the available data. Likewise, there are no records of awards won or year-specific honors attributed to their work.

This profile is based solely on the verified affiliation and geographical location, without available detail on specific academic contributions or scientific output.

Best Publications

  • Learning Bayesian Networks: The Combination of Knowledge and Statistical Data

    David Heckerman;Dan Geiger;David M. Chickering

  • Optimal structure identification with greedy search

    David Maxwell Chickering

  • Learning Bayesian Networks is NP-Complete

    David Maxwell Chickering

  • Learning equivalence classes of bayesian-network structures

    David Maxwell Chickering

  • Large-Sample Learning of Bayesian Networks is NP-Hard

    David Maxwell Chickering;David Heckerman;Christopher Meek

  • Dependency networks for inference, collaborative filtering, and data visualization

    David Heckerman;David Maxwell Chickering;Christopher Meek;Robert Rounthwaite

  • Systems and methods for allocating placement of content items on a rendered page based upon bid value

    David Chickering;Christopher Meek;David Heckerman;Brian Burdick

  • Collaborative filtering utilizing a belief network

    David E. Heckerman;John S. Breese;Eric Horvitz;David Maxwell Chickering

  • A Bayesian approach to learning Bayesian networks with local structure

    David Maxwell Chickering;David Heckerman;Christopher Meek

  • Apparatus and accompanying methods for visualizing clusters of data and hierarchical cluster classifications

    David E. Heckerman;Paul S. Bradley;David M. Chickering;Christopher A. Meek

  • Efficient Approximations for the MarginalLikelihood of Bayesian Networks with Hidden Variables

    David Maxwell Chickering;David Heckerman

  • A transformational characterization of equivalent Bayesian network structures

    David Maxwell Chickering

  • Using predictive user models for language modeling on a personal device with user behavior models based on statistical modeling

    Timothy S. Paek;David M. Chickering

  • Mixtures of bayesian networks

    Bo Thiesson;Christopher A. Meek;David Maxwell Chickering;David Earl Heckerman

  • ModelTracker: Redesigning Performance Analysis Tools for Machine Learning

    Saleema Amershi;Max Chickering;Steven M. Drucker;Bongshin Lee

  • Here or There

    Ben Carterette;Paul N. Bennett;David Maxwell Chickering;Susan T. Dumais

  • Here or there: preference judgments for relevance

    Ben Carterette;Paul N. Bennett;David Maxwell Chickering;Susan T. Dumais

  • Method and system for visualization of clusters and classifications

    David E. Heckerman;David Maxwell Chickering;Usama M. Fayyad;Christopher A. Meek

  • Using temporal data for making recommendations

    Andrew Zimdars;David Maxwell Chickering;Christopher Meek

  • Dialog repair based on discrepancies between user model predictions and speech recognition results

    Timothy S. Paek;David M. Chickering

  • Large-sample learning of bayesian networks is NP-hard

    David Maxwell Chickering;Christopher Meek;David Heckerman

  • Preference Judgments for Relevance

    Ben Carterette;Paul N. Bennett;David Maxwell Chickering;Susan T. Dumais

Frequent Co-Authors

David Heckerman
David Heckerman Microsoft (United States)
Christopher A. Meek
Christopher A. Meek Microsoft (United States)
Eric Horvitz
Eric Horvitz Microsoft (United States)
Robert L. Rounthwaite
Robert L. Rounthwaite Microsoft (United States)
Kamal Jain
Kamal Jain Microsoft (United States)
Alexander G. Gounares
Alexander G. Gounares Microsoft (United States)
Lili Cheng
Lili Cheng Microsoft (United States)
Gary W. Flake
Gary W. Flake Independent Scientist / Consultant, US
Paul N. Bennett
Paul N. Bennett Microsoft (United States)
Dan Geiger
Dan Geiger Technion – Israel Institute of Technology

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