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ESANN
2008
13 years 11 months ago
K-nearest neighbours based on mutual information for incomplete data classification
Incomplete data is a common drawback that machine learning techniques need to deal with when solving real-life classification tasks. One of the most popular procedures for solving ...
Pedro J. García-Laencina, José-Luis ...
ATAL
2004
Springer
14 years 3 months ago
The Advantages of Compromising in Coalition Formation with Incomplete Information
This paper presents protocols and strategies for coalition formation with incomplete information under time constraints. It focuses on strategies for coalition members to distribu...
Sarit Kraus, Onn Shehory, Gilad Taase
SIGMOD
2007
ACM
225views Database» more  SIGMOD 2007»
14 years 10 months ago
From complete to incomplete information and back
Incomplete information arises naturally in numerous data management applications. Recently, several researchers have studied query processing in the context of incomplete informat...
Lyublena Antova, Christoph Koch, Dan Olteanu
DLOG
2011
13 years 1 months ago
Relaxed Abduction: Robust Information Interpretation for Incomplete Models
This paper introduces relaxed abduction, a novel non-standard reasoning task for description logics. Although abductive reasoning over description logic knowledge bases has been ap...
Thomas Hubauer, Steffen Lamparter, Michael Pirker
ECAI
2006
Springer
14 years 1 months ago
An Automated Agent for Bilateral Negotiation with Bounded Rational Agents with Incomplete Information
Many day-to-day tasks require negotiation, mostly under conditions of incomplete information. In particular, the opponent's exact tradeoff between different offers is usually ...
Raz Lin, Sarit Kraus, Jonathan Wilkenfeld, James B...