On Learning from Label Proportions

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Is random model better? on its accuracy and efficiency

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Learning about individuals from group statistics

Hendrik Kuck and Nando de Freitas · 2005

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Learning from aggregate views

B.C. Chen, L. Chen, R. Ramakrishnan, and D.R. Musicant · 2006

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Calibrating noise to sensitivity in private data analysis

C. Dwork, F. McSherry, K. Nissim, and A. Smith · 2006

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Differential privacy

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Supervised learning by training on aggregate outputs

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Neural network learning: Theoretical foundations

Martin Anthony and Peter L Bartlett · 2009

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Estimating labels from label proportions

N. Quadrianto, A.J. Smola, T.S. Caetano, and Q.V. Le · 2009

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SVM classifier estimation from group probabilities

Partial Information and Distribution-Dependence in Supervised Learning Models

Sivan Sabato · 2012

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Multi-instance learning with any hypothesis class

Sivan Sabato and Naftali Tishby · 2012

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Differentially-private learning of low dimensional manifolds

A. Choromanska, K. Choromanski, G. Jagannathan, and C. Monteleoni · 2013

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Adaptive anonymity via b

Krzysztof Choromanski, Tony Jebara, and Kui Tang · 2013

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∝ \propto SVM for learning with label proportions

F. X. Yu, D. Liu, Sanjiv K., T. Jebara, and S.-F. Chang · 2013

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Object-based visual sentiment concept analysis and application

T. Chen, F. X. Yu, J. Chen, Y. Cui, Y.-Y. Chen, and S.-F. Chang · 2014

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