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ICML
2010
IEEE
15 years 7 months ago
Active Learning for Multi-Task Adaptive Filtering
In this paper, we propose an Active Learning (AL) framework for the Multi-Task Adaptive Filtering (MTAF) problem. Specifically, we explore AL approaches to rapidly improve an MTAF...
Abhay Harpale, Yiming Yang
ICML
2010
IEEE
15 years 7 months ago
Simple and Efficient Multiple Kernel Learning by Group Lasso
We consider the problem of how to improve the efficiency of Multiple Kernel Learning (MKL). In literature, MKL is often solved by an alternating approach: (1) the minimization of ...
Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Mic...
ICASSP
2010
IEEE
15 years 7 months ago
Distributed learning in cognitive radio networks: Multi-armed bandit with distributed multiple players
—We consider a cognitive radio network with distributed multiple secondary users, where each user independently searches for spectrum opportunities in multiple channels without e...
Keqin Liu, Qing Zhao

Lab
652views
17 years 6 months ago
Electronic Enterprises Laboratory
Our research is motivated by a strong conviction that business processes in electronic enterprises can be designed to deliver high levels of performance through the use of mathemat...
ICML
2006
IEEE
16 years 7 months ago
Nightmare at test time: robust learning by feature deletion
When constructing a classifier from labeled data, it is important not to assign too much weight to any single input feature, in order to increase the robustness of the classifier....
Amir Globerson, Sam T. Roweis