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ACL
2009
15 years 1 months ago
A Graph-based Semi-Supervised Learning for Question-Answering
We present a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate sentences. Using textual entailment analysis, we obtain entailment sco...
Asli Çelikyilmaz, Marcus Thint, Zhiheng Hua...
CVPR
2009
IEEE
15 years 8 months ago
Efficiently training a better visual detector with sparse eigenvectors
Face detection plays an important role in many vision applications. Since Viola and Jones [1] proposed the first real-time AdaBoost based object detection system, much effort has ...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
15 years 5 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
16 years 4 months ago
Learning optimal ranking with tensor factorization for tag recommendation
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
Steffen Rendle, Leandro Balby Marinho, Alexandros ...
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
15 years 10 months ago
ACOhg: dealing with huge graphs
Ant Colony Optimization (ACO) has been successfully applied to those combinatorial optimization problems which can be translated into a graph exploration. Artificial ants build s...
Enrique Alba, J. Francisco Chicano