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139
Voted
KDD
2004
ACM
135views Data Mining» more  KDD 2004»
16 years 2 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
127
Voted
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 2 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
135
Voted
KDD
2003
ACM
266views Data Mining» more  KDD 2003»
16 years 2 months ago
Applying data mining in investigating money laundering crimes
In this paper, we study the problem of applying data mining to facilitate the investigation of money laundering crimes (MLCs). We have identified a new paradigm of problems --- th...
Zhongfei (Mark) Zhang, John J. Salerno, Philip S. ...
111
Voted
KDD
2002
ACM
127views Data Mining» more  KDD 2002»
16 years 2 months ago
Mining knowledge-sharing sites for viral marketing
Viral marketing takes advantage of networks of influence among customers to inexpensively achieve large changes in behavior. Our research seeks to put it on a firmer footing by mi...
Matthew Richardson, Pedro Domingos
MOBISYS
2008
ACM
16 years 2 months ago
Detecting energy-greedy anomalies and mobile malware variants
Mobile users of computation and communication services have been rapidly adopting battery-powered mobile handhelds, such as PocketPCs and SmartPhones, for their work. However, the...
Hahnsang Kim, Joshua Smith, Kang G. Shin