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» Causal inference using the algorithmic Markov condition
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NIPS
2008
14 years 11 months ago
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...
Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Ma...
ICML
2009
IEEE
15 years 10 months ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani
ICMCS
2007
IEEE
132views Multimedia» more  ICMCS 2007»
15 years 4 months ago
Two-Layer Generative Models for Sport Video Mining
We present a two-layer generative model for sport video mining that is composed of a two-layer observation model. The first layer is the Gaussian mixture model (GMM) using framew...
Yi Ding, Guoliang Fan, W. Bryan
AI
2006
Springer
14 years 10 months ago
Backward-chaining evolutionary algorithms
Starting from some simple observations on a popular selection method in Evolutionary Algorithms (EAs)--tournament selection--we highlight a previously-unknown source of inefficien...
Riccardo Poli, William B. Langdon
CORR
2011
Springer
210views Education» more  CORR 2011»
14 years 1 months ago
Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies
Wireless systems comprised of rechargeable nodes have a significantly prolonged lifetime and are sustainable. A distinct characteristic of these systems is the fact that the node...
Omur Ozel, Kaya Tutuncuoglu, Jing Yang, Sennur Ulu...