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» Active learning in heteroscedastic noise
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ADMA
2009
Springer
246views Data Mining» more  ADMA 2009»
14 years 4 months ago
Semi Supervised Image Spam Hunter: A Regularized Discriminant EM Approach
Image spam is a new trend in the family of email spams. The new image spams employ a variety of image processing technologies to create random noises. In this paper, we propose a s...
Yan Gao, Ming Yang, Alok N. Choudhary
SIGIR
2011
ACM
13 years 19 days ago
Learning to rank from a noisy crowd
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
Abhimanu Kumar, Matthew Lease
IROS
2008
IEEE
125views Robotics» more  IROS 2008»
14 years 4 months ago
Neighborhood denoising for learning high-dimensional grasping manifolds
— Human control of high degree-of-freedom robotic systems, e.g. anthropomorphic robot hands, is often difficult due to the overwhelming number of variables that need to be speci...
Aggeliki Tsoli, Odest Chadwicke Jenkins
UCS
2007
Springer
14 years 3 months ago
Instant Learning Sound Sensor: Flexible Real-World Event Recognition System for Ubiquitous Computing
We propose a smart sound sensor for building context-aware systems that instantly learn and detect events from various kinds of everyday sounds and environmental noise by using sma...
Yuya Negishi, Nobuo Kawaguchi
ISVC
2007
Springer
14 years 4 months ago
Boosting with Temporal Consistent Learners: An Application to Human Activity Recognition
We present a novel boosting algorithm where temporal consistency is addressed in a short-term way. Although temporal correlation of observed data may be an important cue for classi...
Pedro Canotilho Ribeiro, Plinio Moreno, José...