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» Adaptive Learning in Machine Summarization
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ICML
2006
IEEE
16 years 3 months ago
Learning to impersonate
Consider Alice, who is interacting with Bob. Alice and Bob have some shared secret which helps Alice identify Bob-impersonators. Now consider Eve, who knows Alice and Bob, but doe...
Moni Naor, Guy N. Rothblum
123
Voted
ICPR
2010
IEEE
15 years 8 months ago
On-Line Random Naive Bayes for Tracking
—Randomized learning methods (i.e., Forests or Ferns) have shown excellent capabilities for various computer vision applications. However, it was shown that the tree structure in...
Martin Godec, Christian Leistner, Amir Saffari, Ho...
IJCNN
2008
IEEE
15 years 9 months ago
Incremental Common Spatial Pattern algorithm for BCI
— A major challenge in applying machine learning methods to Brain-Computer Interfaces (BCIs) is to overcome the on-line non-stationarity of the data blocks. An effective BCI syst...
Qibin Zhao, Liqing Zhang, Andrzej Cichocki, Jie Li
155
Voted
PAMI
2012
13 years 5 months ago
Task-Driven Dictionary Learning
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Julien Mairal, Francis Bach, Jean Ponce
125
Voted
JMLR
2010
195views more  JMLR 2010»
15 years 29 days ago
Online Learning for Matrix Factorization and Sparse Coding
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...