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» Topic modeling with network regularization
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ICML
2009
IEEE
16 years 6 months 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 6 months 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 11 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 7 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 10 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...