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» Application of Neural Networks in Financial Data Mining
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99
Voted
KDD
2010
ACM
247views Data Mining» more  KDD 2010»
15 years 2 months ago
Metric forensics: a multi-level approach for mining volatile graphs
Advances in data collection and storage capacity have made it increasingly possible to collect highly volatile graph data for analysis. Existing graph analysis techniques are not ...
Keith Henderson, Tina Eliassi-Rad, Christos Falout...
108
Voted
EAAI
2007
90views more  EAAI 2007»
15 years 17 days ago
AI techniques in modelling, assignment, problem solving and optimization
This paper recapitulates the results of a long research on a family of artificial intelligence (AI) methods—relying on, e.g., artificial neural networks and search techniques...
Zsolt János Viharos, Zsolt Kemény
101
Voted
IJCNN
2000
IEEE
15 years 5 months ago
Metrics that Learn Relevance
We introduce an algorithm for learning a local metric to a continuous input space that measures distances in terms of relevance to the processing task. The relevance is defined a...
Samuel Kaski, Janne Sinkkonen
119
Voted
KDD
2008
ACM
224views Data Mining» more  KDD 2008»
16 years 1 months ago
The structure of information pathways in a social communication network
Social networks are of interest to researchers in part because they are thought to mediate the flow of information in communities and organizations. Here we study the temporal dyn...
Gueorgi Kossinets, Jon M. Kleinberg, Duncan J. Wat...
112
Voted
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 1 months ago
Constrained optimization for validation-guided conditional random field learning
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...