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MM
2003
ACM
241views Multimedia» more  MM 2003»
14 years 1 months ago
Invariance in motion analysis of videos
In this paper, we propose an approach that retrieves motion of objects from the videos based on the dynamic time warping of view invariant characteristics. The motion is represent...
Cen Rao, Mubarak Shah, Tanveer Fathima Syeda-Mahmo...
AAAI
2006
13 years 10 months ago
Efficient L1 Regularized Logistic Regression
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
AND
2009
13 years 6 months ago
Discovering voter preferences in blogs using mixtures of topic models
In this paper we propose a new approach to capture the inclination towards a certain election candidate from the contents of blogs and to explain why that inclination may be so. T...
Pradipto Das, Rohini K. Srihari, Smruthi Mukund
IJCV
2008
192views more  IJCV 2008»
13 years 8 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
ICPR
2006
IEEE
14 years 9 months ago
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning
It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
B. Michael Kelm, Chris Pal, Andrew McCallum