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» On the Vulnerability of Large Graphs
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153
Voted
DSN
2007
IEEE
16 years 15 days ago
Architecture-Level Soft Error Analysis: Examining the Limits of Common Assumptions
This paper concerns the validity of a widely used method for estimating the architecture-level mean time to failure (MTTF) due to soft errors. The method first calculates the fai...
Xiaodong Li, Sarita V. Adve, Pradip Bose, Jude A. ...
ICCSA
2003
Springer
15 years 11 months ago
Robust Speaker Recognition Against Utterance Variations
A speaker model in speaker recognition system is to be trained from a large data set gathered in multiple sessions. Large data set requires large amount of memory and computation, ...
JongJoo Lee, JaeYeol Rheem, Ki Yong Lee
185
Voted
ICML
1996
IEEE
16 years 7 months ago
Learning Evaluation Functions for Large Acyclic Domains
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
Justin A. Boyan, Andrew W. Moore
204
Voted
ICML
2007
IEEE
16 years 7 months ago
Entire regularization paths for graph data
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda
RECOMB
2005
Springer
16 years 6 months ago
Graph Theoretical Insights into Evolution of Multidomain Proteins
We study properties of multidomain proteins from a graph theoretical perspective. In particular, we demonstrate connections between properties of the domain overlap graph and certa...
Teresa M. Przytycka, George Davis, Nan Song, Danni...