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ICML
2008
IEEE
14 years 9 months ago
Active kernel learning
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Steven C. H. Hoi, Rong Jin
WWW
2001
ACM
14 years 9 months ago
An intelligent distributed environment for active learning
Active learning is an e ective learning approach. In this paper, we present an intelligent agent assisted environment for active learning. The system is to better support studentc...
Yi Shang, Hongchi Shi, Su-Shing Chen
AAAI
2006
13 years 10 months ago
Reinforcement Learning with Human Teachers: Evidence of Feedback and Guidance with Implications for Learning Performance
As robots become a mass consumer product, they will need to learn new skills by interacting with typical human users. Past approaches have adapted reinforcement learning (RL) to a...
Andrea Lockerd Thomaz, Cynthia Breazeal
ICML
2009
IEEE
14 years 9 months ago
Importance weighted active learning
We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...
Alina Beygelzimer, Sanjoy Dasgupta, John Langford
JMLR
2010
82views more  JMLR 2010»
13 years 3 months ago
Negative Results for Active Learning with Convex Losses
We study the problem of active learning with convex loss functions. We prove that even under bounded noise constraints, the minimax rates for proper active learning are often no b...
Steve Hanneke, Liu Yang