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» Relevant subtask learning by constrained mixture models
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LWA
2007
13 years 9 months ago
Towards Learning User-Adaptive State Models in a Conversational Recommender System
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
Tariq Mahmood, Francesco Ricci
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
ICMCS
2006
IEEE
174views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Web Image Mining Based on Modeling Concept-Sensitive Salient Regions
In this paper, we propose a probabilistic model for web image mining, which is based on concept-sensitive salient regions without human intervene. Our goal is to achieve a middle-...
Jing Liu, Qingshan Liu, Jinqiao Wang, Hanqing Lu, ...
COGSR
2011
109views more  COGSR 2011»
13 years 2 months ago
How groups develop a specialized domain vocabulary: A cognitive multi-agent model
We simulate the evolution of a domain vocabulary in small communities. Empirical data show that human communicators can evolve graphical languages quickly in a constrained task (P...
David Reitter, Christian Lebiere
ICCS
2007
Springer
14 years 1 months ago
Dynamic Tracking of Facial Expressions Using Adaptive, Overlapping Subspaces
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
Dimitris N. Metaxas, Atul Kanaujia, Zhiguo Li