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» Topic modeling with network regularization
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ICML
2009
IEEE
16 years 19 days ago
On primal and dual sparsity of Markov networks
Sparsity is a desirable property in high dimensional learning. The 1-norm regularization can lead to primal sparsity, while max-margin methods achieve dual sparsity. Combining the...
Jun Zhu, Eric P. Xing
KDD
2009
ACM
206views Data Mining» more  KDD 2009»
16 years 11 days ago
Ranking-based clustering of heterogeneous information networks with star network schema
A heterogeneous information network is an information network composed of multiple types of objects. Clustering on such a network may lead to better understanding of both hidden s...
Yizhou Sun, Yintao Yu, Jiawei Han
DCOSS
2005
Springer
15 years 5 months ago
Analysis of Gradient-Based Routing Protocols in Sensor Networks
Abstract. Every physical event results in a natural information gradient in the proximity of the phenomenon. Moreover, many physical phenomena follow the diffusion laws. This natu...
Jabed Faruque, Konstantinos Psounis, Ahmed Helmy
UAI
2008
15 years 1 months ago
Efficient Inference in Persistent Dynamic Bayesian Networks
Numerous temporal inference tasks such as fault monitoring and anomaly detection exhibit a persistence property: for example, if something breaks, it stays broken until an interve...
Tomás Singliar, Denver Dash
DEBS
2007
ACM
15 years 3 months ago
Concepts and models for typing events for event-based systems
Event-based systems are increasingly gaining widespread attention for applications that require integration with loosely coupled and distributed systems for time-critical business...
Szabolcs Rozsnyai, Josef Schiefer, Alexander Schat...