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» Training Methods for Adaptive Boosting of Neural Networks
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IEEEMM
2007
146views more  IEEEMM 2007»
14 years 9 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
75
Voted
ATAL
2006
Springer
15 years 1 months ago
Learning a common language through an emergent interaction topology
We study the effects of various emergent topologies of interaction on the rate of language convergence in a population of communicating agents. The agents generate, parse, and lea...
Samarth Swarup, Kiran Lakkaraju, Les Gasser
ATAL
2007
Springer
15 years 3 months ago
Transfer via inter-task mappings in policy search reinforcement learning
The ambitious goal of transfer learning is to accelerate learning on a target task after training on a different, but related, source task. While many past transfer methods have f...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
IWANN
2007
Springer
15 years 3 months ago
A Novel 2-D Model Approach for the Prediction of Hourly Solar Radiation
In this work, a two-dimensional (2-D) representation of the hourly solar radiation data is proposed. The model enables accurate forecasting using image prediction methods. One year...
Fatih Onur Hocaoglu, Ömer Nezih Gerek, Mehmet...
101
Voted
IROS
2008
IEEE
141views Robotics» more  IROS 2008»
15 years 4 months ago
Active sensing based dynamical object feature extraction
— This paper presents a method to autonomously extract object features that describe their dynamics from active sensing experiences. The model is composed of a dynamics learning ...
Shun Nishide, Tetsuya Ogata, Ryunosuke Yokoya, Jun...