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ICML
2009
IEEE
15 years 4 months ago
Supervised learning from multiple experts: whom to trust when everyone lies a bit
We describe a probabilistic approach for supervised learning when we have multiple experts/annotators providing (possibly noisy) labels but no absolute gold standard. The proposed...
Vikas C. Raykar, Shipeng Yu, Linda H. Zhao, Anna K...
SMC
2007
IEEE
120views Control Systems» more  SMC 2007»
15 years 4 months ago
A data-dependent distance measure for transductive instance-based learning
— We consider learning in a transductive setting using instance-based learning (k-NN) and present a method for constructing a data-dependent distance “metric” using both labe...
Jared Lundell, Dan Ventura
ATAL
2004
Springer
15 years 3 months ago
Time-Extended Policies in Multi-Agent Reinforcement Learning
Many algorithms such as Q-learning successfully address reinforcement learning in single-agent multi-time-step problems. In addition there are methods that address reinforcement l...
Kagan Tumer, Adrian K. Agogino
ESANN
2007
14 years 11 months ago
Convex optimization for the design of learning machines
This paper reviews the recent surge of interest in convex optimization in a context of pattern recognition and machine learning. The main thesis of this paper is that the design of...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
ACCV
2009
Springer
15 years 4 months ago
Interactive Super-Resolution through Neighbor Embedding
Learning based super-resolution can recover high resolution image with high quality. However, building an interactive learning based super-resolution system for general images is e...
Jian Pu, Junping Zhang, Peihong Guo, Xiaoru Yuan