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141
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WACV
2005
IEEE
15 years 9 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
106
Voted
AI
2004
Springer
15 years 9 months ago
Multi-attribute Decision Making in a Complex Multiagent Environment Using Reinforcement Learning with Selective Perception
Abstract. Choosing between multiple alternative tasks is a hard problem for agents evolving in an uncertain real-time multiagent environment. An example of such environment is the ...
Sébastien Paquet, Nicolas Bernier, Brahim C...
132
Voted
ECAI
2008
Springer
15 years 5 months ago
Online Rule Learning via Weighted Model Counting
Online multiplicative weight-update learning algorithms, such as Winnow, have proven to behave remarkably for learning simple disjunctions with few relevant attributes. The aim of ...
Frédéric Koriche
106
Voted
TNN
1998
112views more  TNN 1998»
15 years 3 months ago
A class of competitive learning models which avoids neuron underutilization problem
— In this paper, we study a qualitative property of a class of competitive learning (CL) models, which is called the multiplicatively biased competitive learning (MBCL) model, na...
Clifford Sze-Tsan Choy, Wan-Chi Siu
129
Voted
JMLR
2010
95views more  JMLR 2010»
14 years 10 months ago
Feature Extraction for Machine Learning: Logic-Probabilistic Approach
The paper analyzes peculiarities of preprocessing of learning data represented in object data bases constituted by multiple relational tables with ontology on top of it. Exactly s...
Vladimir Gorodetsky, Vladimir Samoilov