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» An Instance Selection Approach to Multiple Instance Learning
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IJCAI
2001
13 years 10 months ago
Probabilistic Classification and Clustering in Relational Data
Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...
Benjamin Taskar, Eran Segal, Daphne Koller
SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
13 years 10 months ago
Adaptive Informative Sampling for Active Learning
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
Zhenyu Lu, Xindong Wu, Josh Bongard
ICDM
2009
IEEE
150views Data Mining» more  ICDM 2009»
13 years 6 months ago
Filtering and Refinement: A Two-Stage Approach for Efficient and Effective Anomaly Detection
Anomaly detection is an important data mining task. Most existing methods treat anomalies as inconsistencies and spend the majority amount of time on modeling normal instances. A r...
Xiao Yu, Lu An Tang, Jiawei Han
EMNLP
2009
13 years 6 months ago
Semi-Supervised Learning for Semantic Relation Classification using Stratified Sampling Strategy
This paper presents a new approach to selecting the initial seed set using stratified sampling strategy in bootstrapping-based semi-supervised learning for semantic relation class...
Longhua Qian, Guodong Zhou, Fang Kong, Qiaoming Zh...
GECCO
2003
Springer
128views Optimization» more  GECCO 2003»
14 years 2 months ago
Learning Biped Locomotion from First Principles on a Simulated Humanoid Robot Using Linear Genetic Programming
We describe the first instance of an approach for control programming of humanoid robots, based on evolution as the main adaptation mechanism. In an attempt to overcome some of th...
Krister Wolff, Peter Nordin