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» Learning Generative Models via Discriminative Approaches
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107
Voted
ML
2010
ACM
151views Machine Learning» more  ML 2010»
14 years 11 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
110
Voted
IJCAI
2007
15 years 2 months ago
Learning to Walk through Imitation
Programming a humanoid robot to walk is a challenging problem in robotics. Traditional approaches rely heavily on prior knowledge of the robot's physical parameters to devise...
Rawichote Chalodhorn, David B. Grimes, Keith Groch...
142
Voted
CVPR
2009
IEEE
16 years 8 months ago
A Multi-View Probabilistic Model for 3D Object Classes
We propose a novel probabilistic framework for learning visual models of 3D object categories by combining appearance information and geometric constraints. Objects are represen...
Fei-Fei Li 0002, Hao Su, Min Sun, Silvio Savarese
128
Voted
AIRS
2006
Springer
15 years 4 months ago
A Novel Ant-Based Clustering Approach for Document Clustering
Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant Colony Optimization (ACO) is one such algorithm based on s...
Yulan He, Siu Cheung Hui, Yongxiang Sim
PATAT
2004
Springer
130views Education» more  PATAT 2004»
15 years 6 months ago
Learning User Preferences in Distributed Calendar Scheduling
Abstract. Within the field of software agents, there has been increasing interest in automating the process of calendar scheduling in recent years. Calendar (or meeting) schedulin...
Jean Oh, Stephen F. Smith