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JMLR
2010
155views more  JMLR 2010»
15 years 1 months ago
Bayesian Gaussian Process Latent Variable Model
We introduce a variational inference framework for training the Gaussian process latent variable model and thus performing Bayesian nonlinear dimensionality reduction. This method...
Michalis Titsias, Neil D. Lawrence
NETWORK
2010
119views more  NETWORK 2010»
15 years 1 months ago
A multiple failure propagation model in GMPLS-based networks
In this article, a new model to simulate different failure propagation scenarios in GMPLS-based networks is proposed. Several types of failures and malfunctions may spread along t...
Eusebi Calle, J. Ripoll, J. Segovia, Pere Vil&agra...
TNN
2010
216views Management» more  TNN 2010»
15 years 29 days ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok
CORR
2011
Springer
157views Education» more  CORR 2011»
14 years 10 months ago
Large-Scale Convex Minimization with a Low-Rank Constraint
We address the problem of minimizing a convex function over the space of large matrices with low rank. While this optimization problem is hard in general, we propose an efficient...
Shai Shalev-Shwartz, Alon Gonen, Ohad Shamir
SIGIR
2011
ACM
14 years 9 months ago
When documents are very long, BM25 fails!
We reveal that the Okapi BM25 retrieval function tends to overly penalize very long documents. To address this problem, we present a simple yet effective extension of BM25, namel...
Yuanhua Lv, ChengXiang Zhai