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» On the Complexity of Function Learning
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FLAIRS
2003
15 years 1 months ago
Learning from Reinforcement and Advice Using Composite Reward Functions
1 Reinforcement learning has become a widely used methodology for creating intelligent agents in a wide range of applications. However, its performance deteriorates in tasks with s...
Vinay N. Papudesi, Manfred Huber
128
Voted
PRL
2011
14 years 7 months ago
Consistency of functional learning methods based on derivatives
In some real world applications, such as spectrometry, functional models achieve better predictive performances if they work on the derivatives of order m of their inputs rather t...
Fabrice Rossi, Nathalie Villa-Vialaneix
110
Voted
BIBM
2007
IEEE
135views Bioinformatics» more  BIBM 2007»
15 years 7 months ago
Graph Kernel-Based Learning for Gene Function Prediction from Gene Interaction Network
Prediction of gene functions is a major challenge to biologists in the post-genomic era. Interactions between genes and their products compose networks and can be used to infer ge...
Xin Li, Zhu Zhang, Hsinchun Chen, Jiexun Li
IPMI
2011
Springer
14 years 4 months ago
Learning an Atlas of a Cognitive Process in Its Functional Geometry
In this paper we construct an atlas that captures functional characteristics of a cognitive process from a population of individuals. The functional connectivity is encoded in a lo...
Georg Langs, Danial Lashkari, Andrew Sweet, Yanmei...
102
Voted
ICASSP
2009
IEEE
15 years 7 months ago
Functional estimation in Hilbert space for distributed learning in wireless sensor networks
In this paper, we propose a distributed learning strategy in wireless sensor networks. Taking advantage of recent developments on kernel-based machine learning, we consider a new ...
Paul Honeine, Cédric Richard, José C...