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» Learning for Dynamic Subsumption
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JMLR
2006
143views more  JMLR 2006»
14 years 9 months ago
Segmental Hidden Markov Models with Random Effects for Waveform Modeling
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...
Seyoung Kim, Padhraic Smyth
MANSCI
2006
121views more  MANSCI 2006»
14 years 9 months ago
Methodologies and Algorithms for Group-Rankings Decision
The problem of group ranking, a.k.a. rank aggregation, has been studied in contexts varying from sports, to multi-criteria decision making, to machine learning, to ranking web pag...
Dorit S. Hochbaum, Asaf Levin
ALGORITHMICA
2005
76views more  ALGORITHMICA 2005»
14 years 9 months ago
Characterizing History Independent Data Structures
We consider history independent data structures as proposed for study by Naor and Teague [3]. In a history independent data structure, nothing can be learned from the memory repre...
Jason D. Hartline, Edwin S. Hong, Alexander E. Moh...
ISCI
2007
117views more  ISCI 2007»
14 years 9 months ago
Cognitive high level information fusion
Fusion of sensor and communication data currently can only be performed at a late processing stage after sensor and information are formulated as logical statements at appropriate...
Leonid I. Perlovsky
AAI
2002
109views more  AAI 2002»
14 years 9 months ago
Probabilistic Assessment of User's Emotions in Educational Games
We present a probabilistic model to monitor a user's emotions and engagement during the interaction with educational games. We illustrate how our probabilistic model assesses...
Cristina Conati