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» Learning Algorithms for Domain Adaptation
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ICASSP
2011
IEEE
12 years 11 months ago
Adaptation of source-specific dictionaries in Non-Negative Matrix Factorization for source separation
This paper concerns the adaptation of spectrum dictionaries in audio source separation with supervised learning. Supposing that samples of the audio sources to separate are availa...
Xabier Jaureguiberry, Pierre Leveau, Simon Maller,...
AH
2008
Springer
14 years 1 months ago
A Validation Framework for Formal Models in Adaptive Work-Integrated Learning
The focus of my thesis is on the development of a multi-method framework for the validation of formal models (domain model, user model, and teaching model) for adaptive work-integr...
Barbara Kump
IJON
1998
172views more  IJON 1998»
13 years 7 months ago
Blind separation of convolved mixtures in the frequency domain
In this paper we employ information theoretic algorithms, previously used for separating instantaneous mixtures of sources, for separating convolved mixtures in the frequency doma...
Paris Smaragdis
ML
2000
ACM
150views Machine Learning» more  ML 2000»
13 years 7 months ago
Adaptive Retrieval Agents: Internalizing Local Context and Scaling up to the Web
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
Filippo Menczer, Richard K. Belew
ATAL
2009
Springer
14 years 2 months ago
Generalized model learning for reinforcement learning in factored domains
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Todd Hester, Peter Stone