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76
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KDD
2005
ACM
177views Data Mining» more  KDD 2005»
15 years 10 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
14 years 8 months ago
Generalized model learning for Reinforcement Learning on a humanoid robot
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
Todd Hester, Michael Quinlan, Peter Stone
77
Voted
ICCV
2005
IEEE
15 years 3 months ago
Learning Effective Image Metrics from Few Pairwise Examples
We present a new approach to learning image metrics. The main advantage of our method lies in a formulation that requires only a few pairwise examples. Apparently, based on the li...
Hwann-Tzong Chen, Tyng-Luh Liu, Chiou-Shann Fuh
103
Voted
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
15 years 10 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
HICSS
2003
IEEE
118views Biometrics» more  HICSS 2003»
15 years 2 months ago
Lessons Learned from Real DSL Experiments
Over the years, our group, led by Bob Balzer, designed and implemented three domain-specific languages for use by outside people in real situations. The first language described t...
David S. Wile