Sciweavers

6 search results - page 1 / 2
» A Comparison of Model Free versus Model Intensive Approaches...
Sort
View
EMNLP
2009
13 years 2 months ago
A Comparison of Model Free versus Model Intensive Approaches to Sentence Compression
This work introduces a model free approach to sentence compression, which grew out of ideas from Nomoto (2008), and examines how it compares to a state-of-art model intensive appr...
Tadashi Nomoto
ACL
2009
13 years 2 months ago
A Syntax-Free Approach to Japanese Sentence Compression
Conventional sentence compression methods employ a syntactic parser to compress a sentence without changing its meaning. However, the reference compressions made by humans do not ...
Tsutomu Hirao, Jun Suzuki, Hideki Isozaki
IJCNLP
2005
Springer
13 years 10 months ago
Regularisation Techniques for Conditional Random Fields: Parameterised Versus Parameter-Free
Recent work on Conditional Random Fields (CRFs) has demonstrated the need for regularisation when applying these models to real-world NLP data sets. Conventional approaches to regu...
Andrew Smith, Miles Osborne
ACL
2008
13 years 6 months ago
A Generic Sentence Trimmer with CRFs
The paper presents a novel sentence trimmer in Japanese, which combines a non-statistical yet generic tree generation model and Conditional Random Fields (CRFs), to address improv...
Tadashi Nomoto
CLUSTER
2003
IEEE
13 years 10 months ago
Coordinated Checkpoint versus Message Log for Fault Tolerant MPI
— Large Clusters, high availability clusters and Grid deployments often suffer from network, node or operating system faults and thus require the use of fault tolerant programmin...
Aurelien Bouteiller, Pierre Lemarinier, Gér...