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ESWA
2008
169views more  ESWA 2008»
15 years 4 months ago
Predicting opponent's moves in electronic negotiations using neural networks
Electronic negotiation experiments provide a rich source of information about relationships between the negotiators, their individual actions, and the negotiation dynami...
Réal Carbonneau, Gregory E. Kersten, Rustam...
SECON
2010
IEEE
15 years 2 months ago
Deconstructing Interference Relations in WiFi Networks
Abstract--Wireless interference is the major cause of degradation of capacity in 802.11 wireless networks. We present an approach to estimate the interference between nodes and lin...
Anand Kashyap, Utpal Paul, Samir R. Das
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 5 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
ESANN
2006
15 years 6 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
CVPR
2010
IEEE
16 years 1 months ago
Online Multiclass LPBoost
Online boosting is one of the most successful online learning algorithms in computer vision. While many challenging online learning problems are inherently multi-class, online boo...
Amir Saffari, Martin Godec, Thomas Pock, Christian...