David A. McAllester

Publication Activity (10 Years)

Years Active: 1981-2019
Publications (10 Years): 9

Top Venues

CoRR

ECCV (5)

IEEE Trans. Intell. Transp. Syst.

EMNLP

Publications

Hai Wang, Dian Yu, Kai Sun, Jianshu Chen, Dong Yu, David A. McAllester, Dan Roth
Evidence Sentence Extraction for Machine Reading Comprehension. CoNLL (2019)
Hai Wang, Dian Yu, Kai Sun, Jianshu Chen, Dong Yu, Dan Roth, David A. McAllester
Evidence Sentence Extraction for Machine Reading Comprehension. CoRR (2019)
Zewei Chu, Hai Wang, Kevin Gimpel, David A. McAllester
Broad Context Language Modeling as Reading Comprehension. EACL (2) (2017)
Hai Wang, Takeshi Onishi, Kevin Gimpel, David A. McAllester
Emergent Predication Structure in Hidden State Vectors of Neural Readers. Rep4NLP@ACL (2017)
Hai Wang, Takeshi Onishi, Kevin Gimpel, David A. McAllester
Emergent Logical Structure in Vector Representations of Neural Readers. CoRR (2016)
Zewei Chu, Hai Wang, Kevin Gimpel, David A. McAllester
Broad Context Language Modeling as Reading Comprehension. CoRR (2016)
Takeshi Onishi, Hai Wang, Mohit Bansal, Kevin Gimpel, David A. McAllester
Who did What: A Large-Scale Person-Centered Cloze Dataset. EMNLP (2016)
Takeshi Onishi, Hai Wang, Mohit Bansal, Kevin Gimpel, David A. McAllester
Who did What: A Large-Scale Person-Centered Cloze Dataset. CoRR (2016)
Hai Wang, Mohit Bansal, Kevin Gimpel, David A. McAllester
Machine Comprehension with Syntax, Frames, and Semantics. ACL (2) (2015)
David A. McAllester
Implementation and Abstraction in Mathematics. CoRR (2014)
Shubhendu Trivedi, David A. McAllester, Greg Shakhnarovich
Discriminative Metric Learning by Neighborhood Gerrymandering. NIPS (2014)
Koichiro Yamaguchi, David A. McAllester, Raquel Urtasun
Efficient Joint Segmentation, Occlusion Labeling, Stereo and Flow Estimation. ECCV (5) (2014)
David A. McAllester, Satinder P. Singh
Approximate Planning for Factored POMDPs using Belief State Simplification CoRR (2013)
Koichiro Yamaguchi, David A. McAllester, Raquel Urtasun
Robust Monocular Epipolar Flow Estimation. CVPR (2013)
Pedro F. Felzenszwalb, Ross B. Girshick, David A. McAllester, Deva Ramanan
Visual object detection with deformable part models. Commun. ACM 56 (9) (2013)
David A. McAllester
A PAC-Bayesian Tutorial with A Dropout Bound. CoRR (2013)
David A. McAllester, Petri Myllymäki
Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (2008) CoRR (2012)
Koichiro Yamaguchi, Tamir Hazan, David A. McAllester, Raquel Urtasun
Continuous Markov Random Fields for Robust Stereo Estimation. ECCV (5) (2012)
Koichiro Yamaguchi, Tamir Hazan, David A. McAllester, Raquel Urtasun
Continuous Markov Random Fields for Robust Stereo Estimation CoRR (2012)
Hossein Tehrani Niknejad, Akihiro Takeuchi, Seiichi Mita, David A. McAllester
On-Road Multivehicle Tracking Using Deformable Object Model and Particle Filter With Improved Likelihood Estimation. IEEE Trans. Intell. Transp. Syst. 13 (2) (2012)
David A. McAllester, Michael Collins, Fernando Pereira
Case-Factor Diagrams for Structured Probabilistic Modeling CoRR (2012)
Chunzhao Guo, Seiichi Mita, David A. McAllester
Robust Road Detection and Tracking in Challenging Scenarios Based on Markov Random Fields With Unsupervised Learning. IEEE Trans. Intell. Transp. Syst. 13 (3) (2012)
Pedro F. Felzenszwalb, David A. McAllester
The Generalized A* Architecture CoRR (2011)
Jian Peng, Tamir Hazan, David A. McAllester, Raquel Urtasun
Convex Max-Product over Compact Sets for Protein Folding. ICML (2011)
Chunzhao Guo, Seiichi Mita, David A. McAllester
Hierarchical road understanding for intelligent vehicles based on sensor fusion. ITSC (2011)
Ross B. Girshick, Pedro F. Felzenszwalb, David A. McAllester
Object Detection with Grammar Models. NIPS (2011)
David A. McAllester
Generalization bounds and consistency for latent-structural probit and ramp loss. MLSLP (2011)
David A. McAllester, Joseph Keshet
Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss. NIPS (2011)
Joseph Keshet, David A. McAllester, Tamir Hazan
PAC-Bayesian approach for minimization of phoneme error rate. ICASSP (2011)
Chunzhao Guo, Wataru Sato, Long Han, Seiichi Mita, David A. McAllester
Graph-based 2D road representation of 3D point clouds for intelligent vehicles. Intelligent Vehicles Symposium (2011)
Hossein Tehrani Niknejad, Seiichi Mita, David A. McAllester, Takashi Naito
Vision-based vehicle detection for nighttime with discriminately trained mixture of weighted deformable part models. ITSC (2011)
Joseph Keshet, Chih-Chieh Cheng, Mark Stoehr, David A. McAllester
Direct Error Rate Minimization of Hidden Markov Models. INTERSPEECH (2011)
Hossein Tehrani Niknejad, Koji Takahashi, Seiichi Mita, David A. McAllester
Vehicle detection and tracking at nighttime for urban autonomous driving. IROS (2011)
Hossein Tehrani Niknejad, Koji Takahashi, Seiichi Mita, David A. McAllester
Embedded multi-sensors objects detection and tracking for urban autonomous driving. Intelligent Vehicles Symposium (2011)
Chunzhao Guo, Seiichi Mita, David A. McAllester
Adaptive non-planar road detection and tracking in challenging environments using segmentation-based Markov Random Field. ICRA (2011)
János A. Csirik, Michael L. Littman, David A. McAllester, Robert E. Schapire, Peter Stone
Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions CoRR (2011)
Chunzhao Guo, Seiichi Mita, David A. McAllester
A vision system for autonomous vehicle navigation in challenging traffic scenes using integrated cues. ITSC (2010)
Pedro F. Felzenszwalb, Ross B. Girshick, David A. McAllester, Deva Ramanan
Object Detection with Discriminatively Trained Part-Based Models. IEEE Trans. Pattern Anal. Mach. Intell. 32 (9) (2010)
Pedro F. Felzenszwalb, Ross B. Girshick, David A. McAllester
Cascade object detection with deformable part models. CVPR (2010)
David A. McAllester, Tamir Hazan, Joseph Keshet
Direct Loss Minimization for Structured Prediction. NIPS (2010)
Chunzhao Guo, Seiichi Mita, David A. McAllester
MRF-based road detection with unsupervised learning for autonomous driving in changing environments. Intelligent Vehicles Symposium (2010)
Pedro F. Felzenszwalb, Ross B. Girshick, David A. McAllester, Deva Ramanan
Discriminative Latent Variable Models for Object Detection. ICML (2010)
Akihiro Takeuchi, Seiichi Mita, David A. McAllester
On-road vehicle tracking using deformable object model and particle filter with integrated likelihoods. Intelligent Vehicles Symposium (2010)
Chunzhao Guo, Seiichi Mita, David A. McAllester
Lane detection and tracking in challenging environments based on a weighted graph and integrated cues. IROS (2010)
Hoang Trinh, David A. McAllester
Structure and motion from road-driving stereo sequences. CVPR Workshops (2010)
Prahladh Harsha, Rahul Jain, David A. McAllester, Jaikumar Radhakrishnan
The communication complexity of correlation. IEEE Trans. Inf. Theory 56 (1) (2010)
Chunzhao Guo, Seiichi Mita, David A. McAllester
Stereovision-based road boundary detection for intelligent vehicles in challenging scenarios. IROS (2009)
Hoang Trinh, David A. McAllester
Unsupervised Learning of Stereo Vision with Monocular Depth Cues. BMVC (2009)
Alexander T. Ihler, David A. McAllester
Particle Belief Propagation. AISTATS (2009)
Hoang Trinh, David A. McAllester
Particle-Based Belief Propagation for Structure from Motion and Dense Stereo Vision with Unknown Camera Constraints. RobVis (2008)
David A. McAllester, Michael Collins, Fernando Pereira
Case-factor diagrams for structured probabilistic modeling. J. Comput. Syst. Sci. 74 (1) (2008)
Pedro F. Felzenszwalb, David A. McAllester, Deva Ramanan
A discriminatively trained, multiscale, deformable part model. CVPR (2008)
Prahladh Harsha, Rahul Jain, David A. McAllester, Jaikumar Radhakrishnan
The Communication Complexity of Correlation. Computational Complexity Conference (2007)
Pedro F. Felzenszwalb, David A. McAllester
The Generalized A* Architecture. J. Artif. Intell. Res. 29 (2007)
Matthias Blume, David A. McAllester
Sound and complete models of contracts. J. Funct. Program. 16 (4-5) (2006)
Pedro F. Felzenszwalb, David A. McAllester
A Min-Cover Approach for Finding Salient Curves. CVPR Workshops (2006)
Prahladh Harsha, Rahul Jain, David A. McAllester, Jaikumar Radhakrishnan
The communication complexity of correlation. Electron. Colloquium Comput. Complex. 13 (151) (2006)
Yasemin Altun, David A. McAllester, Mikhail Belkin
Margin Semi-Supervised Learning for Structured Variables. NIPS (2005)
Scott Sanner, David A. McAllester
Affine Algebraic Decision Diagrams (AADDs) and their Application to Structured Probabilistic Inference. IJCAI (2005)
John Langford, David A. McAllester
Computable Shell Decomposition Bounds. J. Mach. Learn. Res. 5 (2004)
David A. McAllester, Michael Collins, Fernando Pereira
Case-Factor Diagrams for Structured Probabilistic Modeling. UAI (2004)
Peter L. Bartlett, Michael Collins, Benjamin Taskar, David A. McAllester
Exponentiated Gradient Algorithms for Large-margin Structured Classification. NIPS (2004)
Matthias Blume, David A. McAllester
A sound (and complete) model of contracts. ICFP (2004)
David A. McAllester
Simplified PAC-Bayesian Margin Bounds. COLT (2003)
Peter Stone, Robert E. Schapire, Michael L. Littman, János A. Csirik, David A. McAllester
Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions. J. Artif. Intell. Res. 19 (2003)
David A. McAllester
Joint RTA-TLCA Invited Talk: A Logical Algorithm for ML Type Inference. RTA (2003)
David A. McAllester
PAC-Bayesian Stochastic Model Selection. Mach. Learn. 51 (1) (2003)
David A. McAllester, Luis E. Ortiz
Concentration Inequalities for the Missing Mass and for Histogram Rule Error. J. Mach. Learn. Res. 4 (2003)
David A. McAllester, Luis E. Ortiz
Concentration Inequalities for the Missing Mass and for Histogram Rule Error. NIPS (2002)
Harald Ganzinger, David A. McAllester
Logical Algorithms. ICLP (2002)
Yishay Mansour, David A. McAllester
Boosting Using Branching Programs. J. Comput. Syst. Sci. 64 (1) (2002)
Robert Givan, David A. McAllester
Polynomial-time computation via local inference relations. ACM Trans. Comput. Log. 3 (4) (2002)
Peter Stone, Robert E. Schapire, János A. Csirik, Michael L. Littman, David A. McAllester
ATTac-2001: A Learning, Autonomous Bidding Agent. AMEC (2002)
Robert Givan, David A. McAllester, Carl Witty, Dexter Kozen
Tarskian Set Constraints. Inf. Comput. 174 (2) (2002)
David A. McAllester
On the complexity analysis of static analyses. J. ACM 49 (4) (2002)
Robert E. Schapire, Peter Stone, David A. McAllester, Michael L. Littman, János A. Csirik
Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation. ICML (2002)
David A. McAllester, Deniz Yuret
Alpha-Beta-Conspiracy Search. J. Int. Comput. Games Assoc. 25 (1) (2002)
Sanjoy Dasgupta, Michael L. Littman, David A. McAllester
PAC Generalization Bounds for Co-training. NIPS (2001)
Andrew W. Appel, David A. McAllester
An indexed model of recursive types for foundational proof-carrying code. ACM Trans. Program. Lang. Syst. 23 (5) (2001)
Harald Ganzinger, David A. McAllester
A New Meta-complexity Theorem for Bottom-Up Logic Programs. IJCAR (2001)
Peter Stone, David A. McAllester
An architecture for action selection in robotic soccer. Agents (2001)
Yishay Mansour, David A. McAllester
Boosting Using Branching Programs. COLT (2000)
John Langford, David A. McAllester
Computable Shell Decomposition Bounds. COLT (2000)
Patrick Riley, Peter Stone, David A. McAllester, Manuela M. Veloso
ATT-CMUnited-2000: Third Place Finisher in the RoboCup-2000 Simulator League. RoboCup (2000)
William W. Cohen, Henry A. Kautz, David A. McAllester
Hardening soft information sources. KDD (2000)
David A. McAllester, Robert E. Schapire
On the Convergence Rate of Good-Turing Estimators. COLT (2000)
David A. McAllester
Meta-complexity Theorems: Talk Abstract. CP (2000)
Yishay Mansour, David A. McAllester
Generalization Bounds for Decision Trees. COLT (2000)
David A. McAllester, Peter Stone
Keeping the Ball from CMUnited-99. RoboCup (2000)
Robert Givan, David A. McAllester
Polynomial-time Computation via Local Inference Relations CoRR (2000)
David A. McAllester
World-Modeling vs. World-Axiomatizing. LPNMR (1999)
David A. McAllester, Satinder P. Singh
Approximate Planning for Factored POMDPs using Belief State Simplification. UAI (1999)
Yishay Mansour, David A. McAllester
Boosting with Multi-Way Branching in Decision Trees. NIPS (1999)
David A. McAllester
PAC-Bayesian Model Averaging. COLT (1999)
Richard S. Sutton, David A. McAllester, Satinder P. Singh, Yishay Mansour
Policy Gradient Methods for Reinforcement Learning with Function Approximation. NIPS (1999)
David A. McAllester
On the Complexity Analysis of Static Analyses. SAS (1999)
Steven P. Abney, David A. McAllester, Fernando Pereira
Relating Probabilistic Grammars and Automata. ACL (1999)
David A. McAllester
Some PAC-Bayesian Theorems. Mach. Learn. 37 (3) (1999)
David A. McAllester
Some PAC-Bayesian Theorems. COLT (1998)
Witold Charatonik, David A. McAllester, Damian Niwinski, Andreas Podelski, Igor Walukiewicz
The Horn Mu-calculus. LICS (1998)

David A. McAllester.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

David A. McAllester