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» Modeling the variability of architectural patterns
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ECAI
2004
Springer
15 years 9 months ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana
DSD
2002
IEEE
103views Hardware» more  DSD 2002»
15 years 9 months ago
On the Fundamental Design Gap in Terabit per Second Packet Switching
We discuss the gap we experience in an industrial design path of high-speed packet switches. As bandwidth demand exceeds progress in CMOS technology, system architects are forced ...
M. Verhappen, P. H. A. van der Putten, Jeroen Voet...
ASIAN
2004
Springer
150views Algorithms» more  ASIAN 2004»
15 years 9 months ago
Concurrent Constraint-Based Memory Machines: A Framework for Java Memory Models
A central problem in extending the von Neumann architecture to petaflop computers with millions of hardware threads and with a shared memory is defining the memory model [Lam79,...
Vijay A. Saraswat
TVLSI
2008
139views more  TVLSI 2008»
15 years 4 months ago
Ternary CAM Power and Delay Model: Extensions and Uses
Applications in computer networks often require high throughput access to large data structures for lookup and classification. While advanced algorithms exist to speed these search...
Banit Agrawal, Timothy Sherwood
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
15 years 5 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...