Sciweavers

72 search results - page 6 / 15
» Random search can outperform mutation
Sort
View
60
Voted
IJCNLP
2005
Springer
15 years 3 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
JCDL
2009
ACM
179views Education» more  JCDL 2009»
15 years 4 months ago
Disambiguating authors in academic publications using random forests
Users of digital libraries usually want to know the exact author or authors of an article. But different authors may share the same names, either as full names or as initials and...
Pucktada Treeratpituk, C. Lee Giles
MIR
2005
ACM
140views Multimedia» more  MIR 2005»
15 years 3 months ago
Multiple random walk and its application in content-based image retrieval
In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
Jingrui He, Hanghang Tong, Mingjing Li, Wei-Ying M...
FGR
2011
IEEE
255views Biometrics» more  FGR 2011»
14 years 1 months ago
Beyond simple features: A large-scale feature search approach to unconstrained face recognition
— Many modern computer vision algorithms are built atop of a set of low-level feature operators (such as SIFT [1], [2]; HOG [3], [4]; or LBP [5], [6]) that transform raw pixel va...
David D. Cox, Nicolas Pinto
CEC
2008
IEEE
15 years 4 months ago
Improved Particle Swarm Optimization with low-discrepancy sequences
— Quasirandom or low discrepancy sequences, such as the Van der Corput, Sobol, Faure, Halton (named after their inventors) etc. are less random than a pseudorandom number sequenc...
Millie Pant, Radha Thangaraj, Crina Grosan, Ajith ...