A. Garg

发表

Fusion of global and local information for object detection

Thomas S. Huang, Shivani Agarwal, Ashutosh Garg, 2002, Object recognition supported by user interaction for service robots.

Google news personalization: scalable online collaborative filtering

Abhinandan Das, Mayur Datar, Ashutosh Garg, 2007, WWW '07.

Layered representations for human activity recognition

Eric Horvitz, Nuria Oliver, Ashutosh Garg, 2002, Proceedings. Fourth IEEE International Conference on Multimodal Interfaces.

Facial Expression Recognition from Video Sequences : Temporal and Static Modelling

Thomas S. Huang, N. Sebe, A. Garg, 2002 .

Recent advances in the automatic recognition of audiovisual speech

Chalapathy Neti, Guillaume Gravier, Gerasimos Potamianos, 2003, Proc. IEEE.

Margin distribution and learning algorithms

D. Roth, A. Garg, 2003, ICML 2003.

Generalization Bounds for Linear Learning Algorithm

Sariel Har-Peled, D. Roth, A. Garg, 2001 .

Approximations for the renewal function

J. R. Kalagnanam, A. Garg, J. Kalagnanam, 1998 .

Generalization Bounds for Linear Learning Algorithms

Sariel Har-Peled, D. Roth, A. Garg, 2001 .

Machine Learning in Computer Vision (Computational Imaging and Vision)

Nicu Sebe, Thomas S. Huang, Ashutosh Garg, 2005 .

Hierarchical Representations for Learning and Inferring Office Activity from Multiple Sensory Channels

Eric Horvitz, Ashutosh Garg, E. Horvitz, 2002 .

Margin Distribution and Learning

Dan Roth, Ashutosh Garg, D. Roth, 2003, ICML.

Modeling video using input/output Markov models with application to multi-modal event detection

Thomas S. Huang, Ashutosh Garg, M. R. Naphade, 2003 .

MMIHMM: Maximum Mutual Information Hidden Markov Models

Nuria Oliver, Ashutosh Garg, N. Oliver, 2002, ICML.

Machine Learning in Computer Vision

Nicu Sebe, Thomas S. Huang, Ashutosh Garg, 2006, Computational Imaging and Vision.

Layered representations for learning and inferring office activity from multiple sensory channels

Eric Horvitz, Nuria Oliver, Ashutosh Garg, 2004, Comput. Vis. Image Underst..

Clustering with Model-level Constraints

Shivakumar Vaithyanathan, Ashutosh Garg, David Gondek, 2005, SDM.

A Bayesian framework for combining gene predictions

Vladimir Pavlovic, Simon Kasif, Ashutosh Garg, 2002, Bioinform..

Vision-based overhead view person recognition

Thomas S. Huang, Ashutosh Garg, Ira Cohen, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Facial expression recognition from video sequences

Nicu Sebe, Thomas S. Huang, Michael S. Lew, 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

Emotion recognition using a Cauchy Naive Bayes classifier

Nicu Sebe, Thomas S. Huang, Michael S. Lew, 2002, Object recognition supported by user interaction for service robots.

Facial expression recognition from video sequences: temporal and static modeling

Nicu Sebe, Thomas S. Huang, Lawrence S. Chen, 2003, Comput. Vis. Image Underst..

Boosted learning in dynamic Bayesian networks for multimodal speaker detection

Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, 2003, Proc. IEEE.

A Smoothing Algorithm for Improved Tracking in Clutter and Multitarget Environment

A. K. Mahalanabis, S. Prasad, A. Garg, 1986, 1986 American Control Conference.

Emotion Recognition from Facial Expressions using Multilevel HMM

Thomas S. Huang, Ashutosh Garg, Ira Cohen, 2000 .

Generalization Bounds for Linear Learning Algorithms

Sariel Har-Peled, D. Roth, A. Garg, 2001 .

On generalization bounds, projection profile, and margin distribution

Dan Roth, Sariel Har-Peled, Ashutosh Garg, 2002, ICML.

Understanding Probabilistic Classifiers

Dan Roth, Ashutosh Garg, D. Roth, 2001, ECML.

Classification Approach towards Banking and Sorting Problems

Thomas S. Huang, Ashutosh Garg, Xiang Sean Zhou, 2003, ECML.

Bayesian networks as ensemble of classifiers

Vladimir Pavlovic, Thomas S. Huang, Ashutosh Garg, 2002, Object recognition supported by user interaction for service robots.

Learning Coherent Concepts

Dan Roth, Ashutosh Garg, D. Roth, 2001, ALT.

Multimodal Speaker Detection Using Input/Output Dynamic Bayesian Networks

Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, 2000, ICMI.

Machine Learning in Computer Vision

Thomas S. Huang, N. Sebe, A. Garg, 2006, Computational Imaging and Vision.

Audio-visual speaker detection using dynamic Bayesian networks

Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

Multimodal speaker detection using error feedback dynamic Bayesian networks

Vladimir Pavlovic, James M. Rehg, Thomas S. Huang, 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).