[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Chen et al., 2022 - Google Patents

Dynamic multi-objective ensemble of acquisition functions in batch Bayesian optimization

Chen et al., 2022

View PDF
Document ID
9231622189250492795
Author
Chen J
Luo F
Wang Z
Publication year
Publication venue
Proceedings of the Genetic and Evolutionary Computation Conference Companion

External Links

Snippet

Bayesian optimization (BO) is a typical approach to solve expensive optimization problems. In each iteration of BO, a Gaussian process (GP) model is trained using the previously evaluated solutions; then next candidate solutions for expensive evaluation are …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • G06Q10/04Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F7/00Methods or arrangements for processing data by operating upon the order or content of the data handled
    • 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
    • G06Q10/10Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00Digital computers in general; Data processing equipment in general
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks

Similar Documents

Publication Publication Date Title
Jangir et al. MOMPA: Multi-objective marine predator algorithm for solving multi-objective optimization problems
Rosin Multi-armed bandits with episode context
Romero et al. Learning hybrid Bayesian networks using mixtures of truncated exponentials
Abdul-Rahman et al. An adaptive parameter binary-real coded genetic algorithm for constraint optimization problems: Performance analysis and estimation of optimal control parameters
Saha et al. Space: Structured compression and sharing of representational space for continual learning
Xie et al. Distributed Gaussian processes hyperparameter optimization for big data using proximal ADMM
Hysen et al. Background sampling for multi-scale ensemble habitat selection modeling: Does the number of points matter?
Abraham et al. How many workers to ask? Adaptive exploration for collecting high quality labels
Wu et al. An ensemble surrogate-based coevolutionary algorithm for solving large-scale expensive optimization problems
Eltamaly et al. A novel musical chairs optimization algorithm
Corstjens et al. A multilevel evaluation method for heuristics with an application to the VRPTW
CN111027709B (en) Information recommendation method and device, server and storage medium
Yang et al. A hybrid discrete artificial bee colony algorithm for imaging satellite mission planning
Safarzadegan Gilan et al. Active learning in multi-objective evolutionary algorithms for sustainable building design
Chen et al. Dynamic multi-objective ensemble of acquisition functions in batch Bayesian optimization
Coello Evolutionary multi-objective optimization and its use in finance
Liu et al. An efficient differential evolution via both top collective and p-best information
Danopoulos et al. Transaxx: Efficient transformers with approximate computing
CN115345303A (en) Convolutional neural network weight tuning method, device, storage medium and electronic equipment
Chang et al. Designing a framework for solving multiobjective simulation optimization problems
Abed et al. A hybrid local search algorithm for minimum dominating set problems
Sun et al. Asynchronous parallel surrogate optimization algorithm based on ensemble surrogating model and stochastic response surface method
Wong et al. Ashera; Neural Guided Optimization Modulo Theory
Sid-Lakhdar et al. Deep Gaussian process with multitask and transfer learning for performance optimization
Feng et al. CSDSE: Apply Cooperative Search to Solve the Exploration-Exploitation Dilemma of Design Space Exploration