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» A Spectral Algorithm for Learning Hidden Markov Models
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SIGIR
2009
ACM
14 years 9 days ago
Temporal collaborative filtering with adaptive neighbourhoods
Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
Neal Lathia, Stephen Hailes, Licia Capra
AAAI
2000
13 years 7 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
TMM
2010
270views Management» more  TMM 2010»
13 years 15 days ago
Sequence Multi-Labeling: A Unified Video Annotation Scheme With Spatial and Temporal Context
Abstract--Automatic video annotation is a challenging yet important problem for content-based video indexing and retrieval. In most existing works, annotation is formulated as a mu...
Yuanning Li, YongHong Tian, Ling-Yu Duan, Jingjing...
PKDD
2010
Springer
178views Data Mining» more  PKDD 2010»
13 years 3 months ago
Graph Regularized Transductive Classification on Heterogeneous Information Networks
A heterogeneous information network is a network composed of multiple types of objects and links. Recently, it has been recognized that strongly-typed heterogeneous information net...
Ming Ji, Yizhou Sun, Marina Danilevsky, Jiawei Han...
CSDA
2007
169views more  CSDA 2007»
13 years 5 months ago
A null space method for over-complete blind source separation
In blind source separation, there are M sources that produce sounds independently and continuously over time. These sounds are then recorded by m receivers. The sound recorded by ...
Ray-Bing Chen, Ying Nian Wu