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IJCNN
2008
IEEE
14 years 1 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
AAAI
1996
13 years 8 months ago
Learning Models for Multi-Source Integration
One issue involved in accessing multiple heterogeneous information sources is how to integrate the retrieved data. SIMS, an information mediator, handles this problem by mapping t...
Sheila Tejada, Craig A. Knoblock, Steven Minton
ALT
2003
Springer
13 years 10 months ago
Efficient Learning of Ordered and Unordered Tree Patterns with Contractible Variables
Due to the rapid growth of tree structured data such as Web documents, efficient learning from tree structured data becomes more and more important. In order to represent structura...
Yusuke Suzuki, Takayoshi Shoudai, Satoshi Matsumot...
ICPR
2010
IEEE
13 years 11 months ago
Spatially Regularized Common Spatial Patterns for EEG Classification
In this paper, we propose a new algorithm for BrainComputer Interface (BCI): the Spatially Regularized Common Spatial Patterns (SRCSP). SRCSP is an extension of the famous CSP alg...
Fabien Lotte, Cuntai Guan
MICAI
2004
Springer
14 years 2 days ago
Faster Proximity Searching in Metric Data
A number of problems in computer science can be solved efficiently with the so called memory based or kernel methods. Among this problems (relevant to the AI community) are multime...
Edgar Chávez, Karina Figueroa