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97
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SSPR
2010
Springer
14 years 8 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
90
Voted
ICWSM
2009
14 years 8 months ago
Targeting Sentiment Expressions through Supervised Ranking of Linguistic Configurations
User generated content is extremely valuable for mining market intelligence because it is unsolicited. We study the problem of analyzing users' sentiment and opinion in their...
Jason S. Kessler, Nicolas Nicolov
83
Voted
CVPR
2008
IEEE
16 years 7 days ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...
93
Voted
IMSCCS
2007
IEEE
15 years 4 months ago
Asymmetric Bagging and Feature Selection for Activities Prediction of Drug Molecules
Background: Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cy...
Guo-Zheng Li, Hao-Hua Meng, Mary Qu Yang, Jack Y. ...
95
Voted
UAI
2003
14 years 11 months ago
On the Convergence of Bound Optimization Algorithms
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...