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HPCA
2009
IEEE
16 years 12 days ago
In-Network Snoop Ordering (INSO): Snoopy coherence on unordered interconnects
Realizing scalable cache coherence in the many-core era comes with a whole new set of constraints and opportunities. It is widely believed that multi-hop, unordered on-chip networ...
Niket Agarwal, Li-Shiuan Peh, Niraj K. Jha
KDD
2009
ACM
611views Data Mining» more  KDD 2009»
16 years 12 days ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
MOBIHOC
2009
ACM
16 years 12 days ago
Predict and relay: an efficient routing in disruption-tolerant networks
Routing is one of the most challenging open problems in disruption-tolerant networks (DTNs) because of the shortlived wireless connectivity environment. To deal with this issue, r...
Quan Yuan, Ionut Cardei, Jie Wu
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 8 days ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
16 years 8 days ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales