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» Depth-based inference for functional data
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ICONIP
2007
14 years 11 months ago
Natural Conjugate Gradient in Variational Inference
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
ISMB
1998
14 years 11 months ago
Phylogenetic Inference in Protein Superfamilies: Analysis of SH2 Domains
This workfocuses on the inference of evolutionary relationships in protein superfamilies, and the uses of these relationships to identify keypositions in the structure, to infer a...
Kimmen Sjölander
JMIV
2010
98views more  JMIV 2010»
14 years 8 months ago
Expectations of Random Sets and Their Boundaries Using Oriented Distance Functions
Shape estimation and object reconstruction are common problems in image analysis. Mathematically, viewing objects in the image plane as random sets reduces the problem of shape es...
Hanna K. Jankowski, Larissa I. Stanberry
NIPS
2007
14 years 11 months ago
Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes
Neural spike trains present challenges to analytical efforts due to their noisy, spiking nature. Many studies of neuroscientific and neural prosthetic importance rely on a smooth...
John P. Cunningham, Byron M. Yu, Krishna V. Shenoy...
KDD
2012
ACM
201views Data Mining» more  KDD 2012»
13 years 6 days ago
Low rank modeling of signed networks
Trust networks, where people leave trust and distrust feedback, are becoming increasingly common. These networks may be regarded as signed graphs, where a positive edge weight cap...
Cho-Jui Hsieh, Kai-Yang Chiang, Inderjit S. Dhillo...