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EUROCAST
2007
Springer
182views Hardware» more  EUROCAST 2007»
15 years 9 months ago
A k-NN Based Perception Scheme for Reinforcement Learning
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
José Antonio Martin H., Javier de Lope Asia...
ATAL
2010
Springer
15 years 3 months ago
Inter-robot transfer learning for perceptual classification
We introduce the novel problem of inter-robot transfer learning for perceptual classification of objects, where multiple heterogeneous robots communicate and transfer learned obje...
Zsolt Kira
126
Voted
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
16 years 3 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
159
Voted
TSP
2008
167views more  TSP 2008»
15 years 1 months ago
Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
Kai Ni, John William Paisley, Lawrence Carin, Davi...
JSAC
2010
107views more  JSAC 2010»
15 years 1 months ago
Online learning in autonomic multi-hop wireless networks for transmitting mission-critical applications
Abstract—In this paper, we study how to optimize the transmission decisions of nodes aimed at supporting mission-critical applications, such as surveillance, security monitoring,...
Hsien-Po Shiang, Mihaela van der Schaar