Results 51 to 60 of about 216,131 (169)
Self-Tuning Lam Annealing: Learning Hyperparameters While Problem Solving
Applied Sciences, 2021 The runtime behavior of Simulated Annealing (SA), similar to other metaheuristics, is controlled by hyperparameters. For SA, hyperparameters affect how “temperature” varies over time, and “temperature” in turn affects SA’s decisions on whether or not to ...
Vincent A. Cicirello
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How priors of initial hyperparameters affect Gaussian process regression models
, 2017 The hyperparameters in Gaussian process regression (GPR) model with a specified kernel are often estimated from the data via the maximum marginal likelihood.
Chen, Zexun, Wang, Bo
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Slice sampling covariance hyperparameters of latent Gaussian models [PDF]
, 2010 The Gaussian process (GP) is a popular way to specify dependencies between random variables in a probabilistic model. In the Bayesian framework the covariance structure can be specified using unknown hyperparameters.
Adams, Ryan Prescott, Murray, Iain
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Applied Sciences, 2021 Automated detection of impurities is in demand for evaluating the quality and safety of human cell-processed therapeutic products in regenerative medicine.
Yasunari Matsuzaka +4 more
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An Enhanced Machine Learning Framework for Network Anomaly Detection
AIGiven the increasing volume and sophistication of cyber-attacks, there has always been a need for improved and adaptive real-time intrusion detection systems.
Oumaima Chentoufi +2 more
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IEEE Access, 2020 The work reported in this article explores a novel Particle Swarm Optimization (PSO) tuned Support Vector Regression (SVR) based technique to develop the small-signal behavioral model for GaN High Electron Mobility Transistor (HEMT).
Ahmad Khusro +4 more
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COVIDNet: Implementing Parallel Architecture on Sound and Image for High Efficacy
Future Internet, 2021 The present work relates to the implementation of core parallel architecture in a deep learning algorithm. At present, deep learning technology forms the main interdisciplinary basis of healthcare, hospital hygiene, biological and medicine.
Manickam Murugappan +4 more
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Loopy belief propagation and probabilistic image processing [PDF]
, 2003 Estimation of hyperparameters by maximization of the marginal likelihood in probabilistic image processing is investigated by using the cluster variation method.
Inoue, J., Tanaka, K., Titterington, M.
core
Improving Language Modelling with Noise-contrastive estimation
, 2017 Neural language models do not scale well when the vocabulary is large. Noise-contrastive estimation (NCE) is a sampling-based method that allows for fast learning with large vocabularies.
Grzes, Marek, Liza, Farhana Ferdousi
core +1 more source