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NIPS
1998
13 years 11 months ago
SMEM Algorithm for Mixture Models
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Ge...
AUTOMATICA
2008
93views more  AUTOMATICA 2008»
13 years 10 months ago
An LFT approach to parameter estimation
In this paper we consider a unified framework for parameter estimation problems which arise in a system identification context. In this framework, the parameters to be estimated a...
Kenneth Hsu, Tyrone L. Vincent, Greg Wolodkin, Sun...
JMLR
2008
209views more  JMLR 2008»
13 years 9 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
CORR
2007
Springer
135views Education» more  CORR 2007»
13 years 9 months ago
Detailed Network Measurements Using Sparse Graph Counters: The Theory
— Measuring network flow sizes is important for tasks like accounting/billing, network forensics and security. Per-flow accounting is considered hard because it requires that m...
Yi Lu, Andrea Montanari, Balaji Prabhakar
ICASSP
2011
IEEE
13 years 1 months ago
Near-field array shape calibration
In the important domain of array shape calibration, the near-field case poses a challenging problem due to the array response complexity induced by the range effect. In this pape...
Shuang Wan, Pei-Jung Chung, Bernard Mulgrew