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AAAI
2008
15 years 8 months ago
Classification by Discriminative Regularization
Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a g...
Bin Zhang, Fei Wang, Ta-Hsin Li, Wen Jun Yin, Jin ...
JMLR
2010
104views more  JMLR 2010»
15 years 1 months ago
How to Explain Individual Classification Decisions
After building a classifier with modern tools of machine learning we typically have a black box at hand that is able to predict well for unseen data. Thus, we get an answer to the...
David Baehrens, Timon Schroeter, Stefan Harmeling,...
ICML
2004
IEEE
16 years 7 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
SIGECOM
2011
ACM
259views ECommerce» more  SIGECOM 2011»
14 years 9 months ago
Designing adaptive trading agents
ended abstract summarizes the research presented in Dr. Pardoe’s recently-completed Ph.D. thesis [Pardoe 2011]. The thesis considers how adaptive trading agents can take advantag...
David Pardoe, Peter Stone
ICDE
2008
IEEE
189views Database» more  ICDE 2008»
16 years 26 days ago
Adapting ranking functions to user preference
— Learning to rank has become a popular method for web search ranking. Traditionally, expert-judged examples are the major training resource for machine learned web ranking, whic...
Keke Chen, Ya Zhang, Zhaohui Zheng, Hongyuan Zha, ...