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ICML
2003
IEEE
15 years 10 months ago
Learning on the Test Data: Leveraging Unseen Features
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Benjamin Taskar, Ming Fai Wong, Daphne Koller
ADMA
2010
Springer
271views Data Mining» more  ADMA 2010»
14 years 4 months ago
Exploiting Concept Clumping for Efficient Incremental E-Mail Categorization
We introduce a novel approach to incremental e-mail categorization based on identifying and exploiting "clumps" of messages that are classified similarly. Clumping reflec...
Alfred Krzywicki, Wayne Wobcke
KDD
2008
ACM
174views Data Mining» more  KDD 2008»
15 years 10 months ago
Effective label acquisition for collective classification
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
Mustafa Bilgic, Lise Getoor
EDUTAINMENT
2006
Springer
15 years 1 months ago
Research of Dynamic Terrain in Complex Battlefield Environments
In this paper, we present a novel method for dynamic terrain in battlefield and an efficient plan to simulate crater in the battle. We explore a few methods for dynamic terrain sur...
Xingquan Cai, Fengxia Li, Haiyan Sun, Shouyi Zhan
COLT
1998
Springer
15 years 1 months ago
Improved Boosting Algorithms using Confidence-Rated Predictions
Abstract. We describe several improvements to Freund and Schapire's AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each o...
Robert E. Schapire, Yoram Singer