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80
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NIPS
1998
15 years 1 months ago
Efficient Bayesian Parameter Estimation in Large Discrete Domains
In this paper we examine the problem of estimating the parameters of a multinomial distribution over a large number of discreteoutcomes,most of which do not appearin the training ...
Nir Friedman, Yoram Singer
88
Voted
NIPS
2007
15 years 2 months ago
Modeling homophily and stochastic equivalence in symmetric relational data
This article discusses a latent variable model for inference and prediction of symmetric relational data. The model, based on the idea of the eigenvalue decomposition, represents ...
Peter Hoff
100
Voted
NIPS
2007
15 years 2 months ago
Variational inference for Markov jump processes
Markov jump processes play an important role in a large number of application domains. However, realistic systems are analytically intractable and they have traditionally been ana...
Manfred Opper, Guido Sanguinetti
93
Voted
NIPS
2007
15 years 2 months ago
Non-parametric Modeling of Partially Ranked Data
Statistical models on full and partial rankings of n items are often of limited practical use for large n due to computational consideration. We explore the use of non-parametric ...
Guy Lebanon, Yi Mao
101
Voted
NIPS
2007
15 years 2 months ago
Random Features for Large-Scale Kernel Machines
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
Ali Rahimi, Benjamin Recht