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Bayesian Optimization
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Merge Kernel for Bayesian Optimization on Permutation Space
Lightweight Federated Learning over Wireless Edge Networks
Blind Targeting: Personalization under Third-Party Privacy Constraints
Reinforcement Learning Increases Wind Farm Power Production by Enabling Closed-Loop Collaborative Control
Machine-Learning-Assisted Photonic Device Development: A Multiscale Approach from Theory to Characterization
Feasibility-Driven Trust Region Bayesian Optimization
Fast Bayesian Optimization of Function Networks with Partial Evaluations
Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient?
The Gittins Index: A Design Principle for Decision-Making Under Uncertainty
ORFS-agent: Tool-Using Agents for Chip Design Optimization
Efficient Learning of Vehicle Controller Parameters via Multi-Fidelity Bayesian Optimization: From Simulation to Experiment
ASPO: Constraint-Aware Bayesian Optimization for FPGA-based Soft Processors
Amortized variational transdimensional inference
Distributional encoding for Gaussian process regression with qualitative inputs
Active Illumination Control in Low-Light Environments using NightHawk
Modelling the Effects of Hearing Loss on Neural Coding in the Auditory Midbrain with Variational Conditioning
VirnyFlow: A Design Space for Responsible Model Development
Bridging Quantum and Classical Computing in Drug Design: Architecture Principles for Improved Molecule Generation
Test Automation for Interactive Scenarios via Promptable Traffic Simulation
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration
Constrained Bayesian Optimization under Bivariate Gaussian Process with Application to Cure Process Optimization
Directed Graph Grammars for Sequence-based Learning
Global optimization of graph acquisition functions for neural architecture search
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling
BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL
Causal-PIK: Causality-based Physical Reasoning with a Physics-Informed Kernel
LLaMEA-BO: A Large Language Model Evolutionary Algorithm for Automatically Generating Bayesian Optimization Algorithms
Improving LLM-based Global Optimization with Search Space Partitioning
T^2Agent A Tool-augmented Multimodal Misinformation Detection Agent with Monte Carlo Tree Search
syftr: Pareto-Optimal Generative AI
Composable Cross-prompt Essay Scoring by Merging Models
Spectral Mixture Kernels for Bayesian Optimization
HiLAB: A Hybrid Inverse-Design Framework
Steering Generative Models with Experimental Data for Protein Fitness Optimization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.