701 search results - page 104 / 141 » Self Bounding Learning Algorithms |
JMLR
2006
13 years 7 months ago
2006
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
JMLR
2008
13 years 7 months ago
2008
We describe and analyze an algorithmic framework for online classification where each online trial consists of multiple prediction tasks that are tied together. We tackle the prob...
ICS
2010
Tsinghua U.
13 years 11 months ago
2010
Tsinghua U.
: We study the weight distribution and list-decoding size of Reed-Muller codes. Given a weight parameter, we are interested in bounding the number of Reed-Muller codewords with a w...
COLT
2004
Springer
14 years 1 months ago
2004
Springer
The main goal of this paper is to prove inequalities on the reconstruction error for Kernel Principal Component Analysis. With respect to previous work on this topic, our contribu...
ATAL
2010
Springer
13 years 8 months ago
2010
Springer
Planning how to interact against bounded memory and unbounded memory learning opponents needs different treatment. Thus far, however, work in this area has shown how to design pla...