[go: up one dir, main page]

Krause et al., 2008 - Google Patents

Near-optimal sensor placements in Gaussian processes: Theory, efficient algorithms and empirical studies.

Krause et al., 2008

View PDF
Document ID
13195106274438459070
Author
Krause A
Singh A
Guestrin C
Publication year
Publication venue
Journal of Machine Learning Research

External Links

Snippet

When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to address this task, for example, geometry or disk models, placing sensors at the …
Continue reading at www.jmlr.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386Retrieval requests
    • G06F17/30424Query processing
    • G06F17/30533Other types of queries
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/12Computer systems based on biological models using genetic models
    • G06N3/126Genetic algorithms, i.e. information processing using digital simulations of the genetic system
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme

Similar Documents

Publication Publication Date Title
Krause et al. Near-optimal sensor placements in Gaussian processes: Theory, efficient algorithms and empirical studies.
US11531886B2 (en) Bayesian graph convolutional neural networks
Nguyen et al. Epistemic uncertainty sampling
Koch et al. Tuning and evolution of support vector kernels
Ghahramani Bayesian non-parametrics and the probabilistic approach to modelling
US7421380B2 (en) Gradient learning for probabilistic ARMA time-series models
US7937264B2 (en) Leveraging unlabeled data with a probabilistic graphical model
Taddy et al. Bayesian guided pattern search for robust local optimization
Ten Broeke et al. The use of surrogate models to analyse agent-based models
Figini et al. Corporate default prediction model averaging: A normative linear pooling approach
Moustapha et al. Multi-objective robust optimization using adaptive surrogate models for problems with mixed continuous-categorical parameters
Hajikolaei et al. Decomposition for large-scale global optimization based on quantified variable correlations uncovered by metamodelling
Wang et al. Bayesian optimization
Long et al. Methods and applications of clusterwise linear regression: a survey and comparison
Ghassemi et al. Adaptive in situ model refinement for surrogate-augmented population-based optimization
Zimmerman et al. Copula modeling of serially correlated multivariate data with hidden structures
He et al. Stationary-sparse causality network learning
Wheatley et al. Estimation of the Hawkes process with renewal immigration using the EM algorithm
Wang Stochastic and deterministic algorithms for continuous black-box optimization
Rapley et al. Model-based inferences from adaptive cluster sampling
Lee et al. Dual Graph‐Based Bayesian Network Modeling With Rao‐Blackwellization for Seismic Reliability and Complexity Quantification of Network Connectivity
Idowu et al. Machine learning in pervasive computing
Capdevila et al. Experiments with learning graphical models on text
Huang et al. Variable Selection for Prediction in Clinical Research
Töpfer et al. Online ML Self-adaptation in Face of Traps