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ACL
2009
10 years 11 months ago
Robust Approach to Abbreviating Terms: A Discriminative Latent Variable Model with Global Information
The present paper describes a robust approach for abbreviating terms. First, in order to incorporate non-local information into abbreviation generation tasks, we present both impl...
Xu Sun, Naoaki Okazaki, Jun-ichi Tsujii
PAMI
2010
249views more  PAMI 2010»
10 years 11 months ago
Object Detection with Discriminatively Trained Part-Based Models
—We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-...
Pedro F. Felzenszwalb, Ross B. Girshick, David A. ...
ECCV
2006
Springer
12 years 3 months ago
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
This paper introduces the Located Hidden Random Field (LHRF), a conditional model for simultaneous part-based detection and segmentation of objects of a given class. Given a traini...
Ashish Kapoor, John M. Winn
SIGIR
2004
ACM
11 years 6 months ago
Locality preserving indexing for document representation
Document representation and indexing is a key problem for document analysis and processing, such as clustering, classification and retrieval. Conventionally, Latent Semantic Index...
Xiaofei He, Deng Cai, Haifeng Liu, Wei-Ying Ma
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
11 years 5 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
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