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HIS
2004
13 years 6 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
HIS
2004
13 years 6 months ago
Hybrid Learning Scheme for Data Mining Applications
Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directl...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
HIS
2004
13 years 6 months ago
Stigmergy in Multi Agent Reinforcement Learning
In this paper, we describe how certain aspects of the biological phenomena of stigmergy can be imported into multiagent reinforcement learning (MARL), with the purpose of better e...
Raghav Aras, Alain Dutech, François Charpil...
HIS
2004
13 years 6 months ago
Neural Networks and Belief Logic
Many researchers have observed that neurons process information in an imprecise manner - if a logical inference emerges from neural computation, it is inexact at best. Thus, there...
Yuan Yan Chen, Joseph J. Chen
HIS
2004
13 years 6 months ago
A Case-Based Recommender for Task Assignment in Heterogeneous Computing Systems
Case-based reasoning (CBR) is a knowledge-based problem-solving technique, which is based on reuse of previous experiences. In this paper we propose a new model for static task as...
S. Ghanbari, Mohammad Reza Meybodi, Kambiz Badie