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EACL
2006
ACL Anthology
15 years 1 months ago
Discriminative Sentence Compression with Soft Syntactic Evidence
We present a model for sentence compression that uses a discriminative largemargin learning framework coupled with a novel feature set defined on compressed bigrams as well as dee...
Ryan T. McDonald
JACM
2000
131views more  JACM 2000»
15 years 7 days ago
The soft heap: an approximate priority queue with optimal error rate
A simple variant of a priority queue, called a soft heap, is introduced. The data structure supports the usual operations: insert, delete, meld, and findmin. Its novelty is to beat...
Bernard Chazelle
92
Voted
DSN
2007
IEEE
15 years 6 months 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. ...
90
Voted
CVPR
2000
IEEE
15 years 4 months ago
Learning Patterns from Images by Combining Soft Decisions and Hard Decisions
We present a novel approach for learning patterns (sub-images) shared by multiple images without prior knowledge about the number and the positions of the patterns in the images. ...
Pengyu Hong, Thomas S. Huang, Roy Wang
TCAD
2008
88views more  TCAD 2008»
15 years 10 days ago
Self-Adaptive Data Caches for Soft-Error Reliability
Soft-error induced reliability problems have become a major challenge in designing new generation microprocessors. Due to the on-chip caches' dominant share in die area and tr...
Shuai Wang, Jie S. Hu, Sotirios G. Ziavras