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PRIB
2009
Springer
209views Bioinformatics» more  PRIB 2009»
15 years 9 months ago
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm
For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. An established approach to pursuing supervised learning with ...
Yiming Ying, Colin Campbell, Theodoros Damoulas, M...
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
16 years 2 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
ECML
2004
Springer
15 years 7 months ago
SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
Rong Jin, Huan Liu
ICRA
2007
IEEE
128views Robotics» more  ICRA 2007»
15 years 8 months ago
Adaptive Play Q-Learning with Initial Heuristic Approximation
Abstract— The problem of an effective coordination of multiple autonomous robots is one of the most important tasks of the modern robotics. In turn, it is well known that the lea...
Andriy Burkov, Brahim Chaib-draa
IUI
2006
ACM
15 years 8 months ago
Are two talking heads better than one?: when should use more than one agent in e-learning?
Recent interest in the use of software character agents raises the issue of how many agents should be used in online learning. In this paper we review evidence concerning the rela...
Hua Wang, Mark H. Chignell, Mitsuru Ishizuka