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ICDE
2008
IEEE
137views Database» more  ICDE 2008»
14 years 11 months ago
Stop Chasing Trends: Discovering High Order Models in Evolving Data
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...
KDD
2004
ACM
135views Data Mining» more  KDD 2004»
14 years 10 months ago
Discovering additive structure in black box functions
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
Giles Hooker
WSDM
2010
ACM
214views Data Mining» more  WSDM 2010»
14 years 7 months ago
Pairwise Interaction Tensor Factorization for Personalized Tag Recommendation
Tagging plays an important role in many recent websites. Recommender systems can help to suggest a user the tags he might want to use for tagging a specific item. Factorization mo...
Steffen Rendle, Lars Schmidt-Thieme
WSDM
2010
ACM
197views Data Mining» more  WSDM 2010»
14 years 4 months ago
Beyond DCG: user behavior as a predictor of a successful search
Web search engines are traditionally evaluated in terms of the relevance of web pages to individual queries. However, relevance of web pages does not tell the complete picture, si...
Ahmed Hassan, Rosie Jones, Kristina Lisa Klinkner
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 4 months ago
Primal sparse Max-margin Markov networks
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
Jun Zhu, Eric P. Xing, Bo Zhang