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ICANN
2011
Springer
14 years 5 months ago
Learning from Multiple Annotators with Gaussian Processes
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Perry Groot, Adriana Birlutiu, Tom Heskes
94
Voted
ISCAS
2006
IEEE
100views Hardware» more  ISCAS 2006»
15 years 7 months ago
Unequal authenticity protection (UAP) for rate-distortion-optimized secure streaming of multimedia over wireless networks
— This paper presents a new notion of authenticating degraded multimedia content streamed over wireless networks – Unequal Authenticity Protection (UAP). Multimedia content dif...
Zhi Li, Qibin Sun, Yong Lian
100
Voted
ICML
2002
IEEE
16 years 2 months ago
Learning from Scarce Experience
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
Leonid Peshkin, Christian R. Shelton
134
Voted
NECO
1998
168views more  NECO 1998»
15 years 1 months ago
Constructive Incremental Learning from Only Local Information
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, t...
Stefan Schaal, Christopher G. Atkeson
ICRA
2010
IEEE
116views Robotics» more  ICRA 2010»
15 years 11 days ago
Learning visibility of landmarks for vision-based localization
— We aim to perform robust and fast vision-based localization using a pre-existing large map of the scene. A key step in localization is associating the features extracted from t...
Pablo Fernández Alcantarilla, Sang Min Oh, ...