Papers Bayesian Optimization
“Bayesian Optimization” 태그가 달린 논문 1,900편 · 필터 해제
Wasserstein Barycenter Gaussian Process based Bayesian Optimization
Gaussian Process based Bayesian Optimization is a widely applied algorithm to learn and optimize under uncertainty, well-known for its sample efficiency. However, recently -- and more frequently -- research studies have …
Bayesian OptimizationGaussian ProcessesData-Efficient Automatic Shaping of Liquid Droplets on an Air-Ferrofluid Interface with Bayesian Optimization
Manipulating the shape of a liquid droplet is essential for a wide range of applications in medicine and industry. However, existing methods are typically limited to generating simple shapes, such as ellipses, or rely on…
Bayesian OptimizationConcave shapesAdaptive Linear Embedding for Nonstationary High-Dimensional Optimization
Bayesian Optimization (BO) in high-dimensional spaces remains fundamentally limited by the curse of dimensionality and the rigidity of global low-dimensional assumptions. While Random EMbedding Bayesian Optimization (REM…
Bayesian OptimizationConvergence Rates of Constrained Expected Improvement
Constrained Bayesian optimization (CBO) methods have seen significant success in black-box optimization with constraints, and one of the most commonly used CBO methods is the constrained expected improvement (CEI) algori…
Bayesian OptimizationGaussian ProcessesConstrained Preferential Bayesian Optimization and Its Application in Banner Ad Design
Preferential Bayesian optimization (PBO) is a variant of Bayesian optimization that observes relative preferences (e.g., pairwise comparisons) instead of direct objective values, making it especially suitable for human-i…
Bayesian OptimizationBidirectional Information Flow (BIF) -- A Sample Efficient Hierarchical Gaussian Process for Bayesian Optimization
Hierarchical Gaussian Process (H-GP) models divide problems into different subtasks, allowing for different models to address each part, making them well-suited for problems with inherent hierarchical structure. However,…
Bayesian OptimizationComparative Analysis of Black-Box Optimization Methods for Weather Intervention Design
As climate change increases the threat of weather-related disasters, research on weather control is gaining importance. The objective of weather control is to mitigate disaster risks by administering interventions with o…
Bayesian OptimizationEfficient ExplorationModel Predictive ControlInterim Report on Human-Guided Adaptive Hyperparameter Optimization with Multi-Fidelity Sprints
This case study applies a phased hyperparameter optimization process to compare multitask natural language model variants that utilize multiphase learning rate scheduling and optimizer parameter grouping. We employ short…
Bayesian OptimizationHyperparameter OptimizationJoint Entity and Relation ExtractionLanguage Modeling+3Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review
Bayesian inference has many advantages in decision making of agents (e.g. robotics/simulative agent) over a regular data-driven black-box neural network: Data-efficiency, generalization, interpretability, and safety wher…
Active LearningBayesian InferenceBayesian OptimizationDecision Making+4Interpretable SHAP-bounded Bayesian Optimization for Underwater Acoustic Metamaterial Coating Design
We developed an interpretability informed Bayesian optimization framework to optimize underwater acoustic coatings based on polyurethane elastomers with embedded metamaterial features. A data driven model was employed to…
Bayesian OptimizationEfficient ExplorationA Computational Approach to Epilepsy Treatment: An AI-optimized Global Natural Product Prescription System
Epilepsy is a prevalent neurological disease with millions of patients worldwide. Many patients have turned to alternative medicine due to the limited efficacy and side effects of conventional antiepileptic drugs. In thi…
Bayesian OptimizationDevice-Free Localization Using Multi-Link MIMO Channels in Distributed Antenna Networks
This paper presented a novel device-free localization (DFL) framework based on distributed antenna networks (DANs), targeting integrated sensing and communication (ISAC) in future 6G radio access networks (RANs). In the …
Bayesian OptimizationDiversityImage ReconstructionIntegrated sensing and communication+1Systematic Evaluation of Initial States and Exploration-Exploitation Strategies in PID Auto-Tuning: A Framework-Driven Approach Applied on Mobile Robots
PID controllers are widely used in control systems because of their simplicity and effectiveness. Although advanced optimization techniques such as Bayesian Optimization and Differential Evolution have been applied to ad…
Bayesian OptimizationScalable Unit Harmonization in Medical Informatics Using Bi-directional Transformers and Bayesian-Optimized BM25 and Sentence Embedding Retrieval
Objective: To develop and evaluate a scalable methodology for harmonizing inconsistent units in large-scale clinical datasets, addressing a key barrier to data interoperability. Materials and Methods: We designed a novel…
Bayesian OptimizationInformation RetrievalRe-RankingRetrieval+4Adaptive Replication Strategies in Trust-Region-Based Bayesian Optimization of Stochastic Functions
We develop and analyze a method for stochastic simulation optimization relying on Gaussian process models within a trust-region framework. We are interested in the case when the variance of the objective function is larg…
Bayesian OptimizationDynamic Fisher-weighted Model Merging via Bayesian Optimization
The fine-tuning of pre-trained language models has resulted in the widespread availability of task-specific models. Model merging offers an efficient way to create multi-task models by combining these fine-tuned models a…
Bayesian OptimizationDemonstration of an AI-driven workflow for dynamic x-ray spectroscopy
X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but requires collecting data at many energy po…
Bayesian OptimizationLatent Bayesian Optimization via Autoregressive Normalizing Flows
Bayesian Optimization (BO) has been recognized for its effectiveness in optimizing expensive and complex objective functions. Recent advancements in Latent Bayesian Optimization (LBO) have shown promise by integrating ge…
Bayesian OptimizationRisk-aware black-box portfolio construction using Bayesian optimization with adaptive weighted Lagrangian estimator
Existing portfolio management approaches are often black-box models due to safety and commercial issues in the industry. However, their performance can vary considerably whenever market conditions or internal trading str…
Bayesian OptimizationManagementAI-Powered Agile Analog Circuit Design and Optimization
Artificial intelligence (AI) techniques are transforming analog circuit design by automating device-level tuning and enabling system-level co-optimization. This paper integrates two approaches: (1) AI-assisted transistor…
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