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» Adaptive Learning from Evolving Data Streams
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JMLR
2012
13 years 3 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
GLVLSI
1998
IEEE
124views VLSI» more  GLVLSI 1998»
15 years 5 months ago
Non-Refreshing Analog Neural Storage Tailored for On-Chip Learning
In this research, we devised a new simple technique for statically holding analog weights, which does not require periodic refreshing. It further contains a mechanism to locally u...
Bassem A. Alhalabi, Qutaibah M. Malluhi, Rafic A. ...
ML
2010
ACM
135views Machine Learning» more  ML 2010»
14 years 7 months ago
Multi-domain learning by confidence-weighted parameter combination
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Mark Dredze, Alex Kulesza, Koby Crammer
124
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ICNP
2003
IEEE
15 years 6 months ago
Resilient Peer-to-Peer Streaming
We consider the problem of distributing “live” streaming media content to a potentially large and highly dynamic population of hosts. Peer-to-peer content distribution is attr...
Venkata N. Padmanabhan, Helen J. Wang, Philip A. C...
PR
2010
156views more  PR 2010»
14 years 11 months ago
Semi-supervised clustering with metric learning: An adaptive kernel method
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
Xuesong Yin, Songcan Chen, Enliang Hu, Daoqiang Zh...