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» Exploiting Deep Structure
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NIPS
2003
15 years 8 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
ISMB
1997
15 years 8 months ago
Standardized Representations of the Literature: Combining Diverse Sources of Ribosomal Data
We are building a knowledge base (KB) of published structural data on the 30s ribosomal subunit in prokaryotes. Our KB is distinguished by a standardized representation of biologi...
Russ B. Altman, Neil F. Abernethy, Richard O. Chen
BMCBI
2007
128views more  BMCBI 2007»
15 years 6 months ago
Model order selection for bio-molecular data clustering
Background: Cluster analysis has been widely applied for investigating structure in bio-molecular data. A drawback of most clustering algorithms is that they cannot automatically ...
Alberto Bertoni, Giorgio Valentini
SIGMETRICS
2011
ACM
178views Hardware» more  SIGMETRICS 2011»
14 years 9 months ago
Soft error benchmarking of L2 caches with PARMA
The amount of charge stored in an SRAM cell shrinks rapidly with each technology generation thus increasingly exposing caches to soft errors. Benchmarking the FIT rate of caches d...
Jinho Suh, Mehrtash Manoochehri, Murali Annavaram,...
HPCA
2008
IEEE
16 years 7 months ago
Address-branch correlation: A novel locality for long-latency hard-to-predict branches
Hard-to-predict branches depending on longlatency cache-misses have been recognized as a major performance obstacle for modern microprocessors. With the widening speed gap between...
Hongliang Gao, Yi Ma, Martin Dimitrov, Huiyang Zho...