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CIKM
2009
Springer
14 years 24 days ago
Adaptive relevance feedback in information retrieval
Relevance Feedback has proven very effective for improving retrieval accuracy. A difficult yet important problem in all relevance feedback methods is how to optimally balance the...
Yuanhua Lv, ChengXiang Zhai
ICTAI
2007
IEEE
14 years 16 days ago
Multi-agent Reinforcement Learning Using Strategies and Voting
Multiagent learning attracts much attention in the past few years as it poses very challenging problems. Reinforcement Learning is an appealing solution to the problems that arise...
Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlah...
ICPR
2000
IEEE
13 years 10 months ago
Integrating Unlabeled Images for Image Retrieval Based on Relevance Feedback
Retrieval techniques based on pure similarity metrics are often suffered from the scales of image features. An alternative approach is to learn a mapping based on queries and rele...
Ying Wu, Qi Tian, Thomas S. Huang
ECAI
2010
Springer
13 years 7 months ago
Case-Based Multiagent Reinforcement Learning: Cases as Heuristics for Selection of Actions
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Multiagent Reinforcement Learning algorithms, combining Case-Based Reasoning...
Reinaldo A. C. Bianchi, Ramon López de M&aa...
CIVR
2006
Springer
186views Image Analysis» more  CIVR 2006»
13 years 10 months ago
Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure
Abstract. Interactively learning from a small sample of unlabeled examples is an enormously challenging task. Relevance feedback and more recently active learning are two standard ...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...