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121
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STOC
2007
ACM
112views Algorithms» more  STOC 2007»
16 years 3 months ago
Smooth sensitivity and sampling in private data analysis
We introduce a new, generic framework for private data analysis. The goal of private data analysis is to release aggregate information about a data set while protecting the privac...
Kobbi Nissim, Sofya Raskhodnikova, Adam Smith
121
Voted
NIPS
2003
15 years 4 months ago
Ambiguous Model Learning Made Unambiguous with 1/f Priors
What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the a...
Gurinder S. Atwal, William Bialek
102
Voted
ICML
2001
IEEE
16 years 3 months ago
A Unified Loss Function in Bayesian Framework for Support Vector Regression
In this paper, we propose a unified non-quadratic loss function for regression known as soft insensitive loss function (SILF). SILF is a flexible model and possesses most of the d...
Wei Chu, S. Sathiya Keerthi, Chong Jin Ong
128
Voted
UCS
2007
Springer
15 years 8 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
125
Voted
IJCNN
2006
IEEE
15 years 8 months ago
A Variational EM Approach to Predicting Uncertainty in Supervised Learning
— In many applications of supervised learning, the conditional average of the target variables is not sufficient for prediction. The dependencies between the explanatory variabl...
Markus Harva