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DIS
2010
Springer
15 years 5 months ago
Speeding Up and Boosting Diverse Density Learning
Abstract. In multi-instance learning, each example is described by a bag of instances instead of a single feature vector. In this paper, we revisit the idea of performing multi-ins...
James R. Foulds, Eibe Frank
JMLR
2010
132views more  JMLR 2010»
15 years 1 months ago
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mu...
CORR
2011
Springer
182views Education» more  CORR 2011»
14 years 10 months ago
Adaptively Learning the Crowd Kernel
We introduce an algorithm that, given n objects, learns a similarity matrix over all n2 pairs, from crowdsourced data alone. The algorithm samples responses to adaptively chosen t...
Omer Tamuz, Ce Liu, Serge Belongie, Ohad Shamir, A...
ICPR
2008
IEEE
16 years 7 months ago
Component-wise parameter smoothing for learning mixture models
In this paper, we propose a novel component-wise smoothing algorithm that constructs a hierarchy (or family) of smoothened log-likelihood surfaces. Our approach first smoothens th...
Bala Rajaratnam, Chandan K. Reddy
ISDA
2009
IEEE
16 years 1 months ago
Postponed Updates for Temporal-Difference Reinforcement Learning
This paper presents postponed updates, a new strategy for TD methods that can improve sample efficiency without incurring the computational and space requirements of model-based ...
Harm van Seijen, Shimon Whiteson