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ECCV
2006
Springer
16 years 8 months ago
Learning to Combine Bottom-Up and Top-Down Segmentation
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
Anat Levin, Yair Weiss
ICML
1995
IEEE
16 years 7 months ago
Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem
In this paper we introduce Ant-Q, a family of algorithms which present many similarities with Q-learning (Watkins, 1989), and which we apply to the solution of symmetric and asymm...
Luca Maria Gambardella, Marco Dorigo
WWW
2005
ACM
16 years 7 months ago
Automatically learning document taxonomies for hierarchical classification
While several hierarchical classification methods have been applied to web content, such techniques invariably rely on a pre-defined taxonomy of documents. We propose a new techni...
Kunal Punera, Suju Rajan, Joydeep Ghosh
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 7 months ago
Catching the drift: learning broad matches from clickthrough data
Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Eff...
Sonal Gupta, Mikhail Bilenko, Matthew Richardson
KDD
2002
ACM
93views Data Mining» more  KDD 2002»
16 years 7 months ago
Interactive deduplication using active learning
Deduplication is a key operation in integrating data from multiple sources. The main challenge in this task is designing a function that can resolve when a pair of records refer t...
Sunita Sarawagi, Anuradha Bhamidipaty