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PRIB
2009
Springer
209views Bioinformatics» more  PRIB 2009»
15 years 4 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...
SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
15 years 4 months ago
An improved immune Q-learning algorithm
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
IJCNN
2000
IEEE
15 years 1 months ago
Unsupervised Classification of Complex Clusters in Networks of Spiking Neurons
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
Sander M. Bohte, Johannes A. La Poutré, Joo...
CVPR
2004
IEEE
15 years 12 months ago
Super-Resolution through Neighbor Embedding
In this paper, we propose a novel method for solving single-image super-resolution problems. Given a low-resolution image as input, we recover its highresolution counterpart using...
Hong Chang, Dit-Yan Yeung, Yimin Xiong
ICIP
2008
IEEE
15 years 11 months ago
Face hallucination VIA sparse coding
In this paper, we address the problem of hallucinating a high resolution face given a low resolution input face. The problem is approached through sparse coding. To exploit the fa...
Jianchao Yang, Hao Tang, Yi Ma, Thomas S. Huang