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CVPR
2010
IEEE
14 years 10 months ago
Boosting for transfer learning with multiple sources
Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a target domain, where the available data is scarce. Th...
Yi Yao, Gianfranco Doretto
IJON
2006
72views more  IJON 2006»
14 years 10 months ago
Extraction of a source signal whose kurtosis value lies in a specific range
In many applications extraction of source signals of interest from observed signals maybe is a more feasible approach than simultaneous separation of all the source signals, since...
Zhi-Lin Zhang, Zhang Yi
TSP
2008
166views more  TSP 2008»
14 years 9 months ago
A Convex Analysis Framework for Blind Separation of Non-Negative Sources
This paper presents a new framework for blind source separation (BSS) of non-negative source signals. The proposed framework, referred herein to as convex analysis of mixtures of ...
Tsung-Han Chan, Wing-Kin Ma, Chong-Yung Chi, Yue W...
CSMR
2010
IEEE
14 years 5 months ago
Co-evolving Annotations and Source Code through Smart Annotations
Annotations are a means to attach additional meta data to the source code of a system. Nowadays, more and more technologies rely on the presence of such annotations in the source c...
Andy Kellens, Carlos Noguera, Kris De Schutter, Co...
PE
2008
Springer
108views Optimization» more  PE 2008»
14 years 10 months ago
Rate-optimal schemes for Peer-to-Peer live streaming
In this paper we consider the problem of sending data in real time from information sources to sets of receivers, using peer-to-peer communications. We consider several models of ...
Laurent Massoulié, Andrew Twigg