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» Learning Behavior Models for Hybrid Timed Systems
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AAAI
2012
13 years 6 months ago
A Sequential Decision Approach to Ordinal Preferences in Recommender Systems
We propose a novel sequential decision approach to modeling ordinal ratings in collaborative filtering problems. The rating process is assumed to start from the lowest level, eva...
Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
RTCSA
2007
IEEE
15 years 10 months ago
Activity Recognition Based on Semi-supervised Learning
Activity recognition is a hot topic in context-aware computing. In activity recognition, machine learning techniques have been widely applied to learn the activity models from lab...
Donghai Guan, Weiwei Yuan, Young-Koo Lee, Andrey G...
SDM
2003
SIAM
123views Data Mining» more  SDM 2003»
15 years 5 months ago
Fast Online SVD Revisions for Lightweight Recommender Systems
The singular value decomposition (SVD) is fundamental to many data modeling/mining algorithms, but SVD algorithms typically have quadratic complexity and require random access to ...
Matthew Brand
SAC
2004
ACM
15 years 9 months ago
Forest trees for on-line data
This paper presents an hybrid adaptive system for induction of forest of trees from data streams. The Ultra Fast Forest Tree system (UFFT) is an incremental algorithm, with consta...
João Gama, Pedro Medas, Ricardo Rocha
ISCAS
2002
IEEE
141views Hardware» more  ISCAS 2002»
15 years 9 months ago
Power characterization of digital filters implemented on FPGA
The evaluation of power consumption in complex digital systems is a hard task that normally requires long simulation time and complicated models. In this work, we obtain power con...
Gian-Carlo Cardarilli, Andrea Del Re, Alberto Nann...