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NIPS
2007
15 years 8 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...
NIPS
2007
15 years 8 months ago
Regularized Boost for Semi-Supervised Learning
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
Ke Chen 0001, Shihai Wang
NIPS
2007
15 years 8 months ago
Fast Variational Inference for Large-scale Internet Diagnosis
Web servers on the Internet need to maintain high reliability, but the cause of intermittent failures of web transactions is non-obvious. We use approximate Bayesian inference to ...
John C. Platt, Emre Kiciman, David A. Maltz
AAAI
2004
15 years 8 months ago
Compressing Pattern Databases
A pattern database is a heuristic function stored as a lookup table which stores the lengths of optimal solutions for instances of subproblems. All previous pattern databases had ...
Ariel Felner, Ram Meshulam, Robert C. Holte, Richa...
ESANN
2006
15 years 8 months ago
Learning for stochastic dynamic programming
Abstract. We present experimental results about learning function values (i.e. Bellman values) in stochastic dynamic programming (SDP). All results come from openDP (opendp.sourcef...
Sylvain Gelly, Jérémie Mary, Olivier...
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