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JCB
2002
70views more  JCB 2002»
15 years 6 months ago
Strong Feature Sets from Small Samples
For small samples, classi er design algorithms typically suffer from over tting. Given a set of features, a classi er must be designed and its error estimated. For small samples, ...
Seungchan Kim, Edward R. Dougherty, Junior Barrera...
WSDM
2009
ACM
136views Data Mining» more  WSDM 2009»
16 years 1 months ago
Mining common topics from multiple asynchronous text streams
Text streams are becoming more and more ubiquitous, in the forms of news feeds, weblog archives and so on, which result in a large volume of data. An effective way to explore the...
Xiang Wang 0002, Kai Zhang, Xiaoming Jin, Dou Shen
ABIALS
2008
Springer
16 years 1 months ago
The Cognitive Body: From Dynamic Modulation to Anticipation
Abstract— Starting from the situated and embodied perspective on the study of biological cognition as a source of inspiration, this paper programmatically outlines a path towards...
Alberto Montebelli, Robert Lowe, Tom Ziemke
NEUROSCIENCE
2001
Springer
15 years 11 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar
DIALM
2008
ACM
179views Algorithms» more  DIALM 2008»
15 years 8 months ago
Distance graphs: from random geometric graphs to Bernoulli graphs and between
A random geometric graph G(n, r) is a graph resulting from placing n points uniformly at random on the unit area disk, and connecting two points iff their Euclidean distance is at ...
Chen Avin