Copertina

MOCA-HESP: Meta High-dimensional Bayesian Optimization for Combinatorial and Mixed Spaces via Hyper-ellipsoid Partitioning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ngo, Lam, Ha, Huong, Chan, Jeffrey, Zhang, Hongyu
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided Direction Lines and Subspace Embeddings
di: Ngo, Lam, et al.
Pubblicazione: (2024)

High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy
di: Ngo, Lam, et al.
Pubblicazione: (2024)

MOBO-OSD: Batch Multi-Objective Bayesian Optimization via Orthogonal Search Directions
di: Ngo, Lam, et al.
Pubblicazione: (2025)

An Empirical Study on Ensemble-Based Transfer Learning Bayesian Optimisation with Mixed Variable Types
di: Trinkle, Natasha, et al.
Pubblicazione: (2026)

Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces
di: Papenmeier, Leonard, et al.
Pubblicazione: (2023)

Provably Efficient Bayesian Optimization with Unknown Gaussian Process Hyperparameter Estimation
di: Ha, Huong, et al.
Pubblicazione: (2023)

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
di: Tran-The, Hung, et al.
Pubblicazione: (2020)

Combinatorial Bandit Bayesian Optimization for Tensor Outputs
di: Huang, Jingru, et al.
Pubblicazione: (2026)

Moco: A Learnable Meta Optimizer for Combinatorial Optimization
di: Dernedde, Tim, et al.
Pubblicazione: (2024)

High dimensional Bayesian Optimization via Condensing-Expansion Projection
di: Lu, Jiaming, et al.
Pubblicazione: (2024)

Pseudo-Bayesian Optimization
di: Chen, Haoxian, et al.
Pubblicazione: (2023)

Conformal prediction for multi-dimensional time series by ellipsoidal sets
di: Xu, Chen, et al.
Pubblicazione: (2024)

Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
di: Jin, Yanhao, et al.
Pubblicazione: (2024)

Designing Active Tether-Net Systems for Space Debris Capture with Graph-Learning-Aided Mixed-Combinatorial Optimization
di: Liu, Feng, et al.
Pubblicazione: (2026)

Variational Combinatorial Sequential Monte Carlo for Bayesian Phylogenetics in Hyperbolic Space
di: Chen, Alex, et al.
Pubblicazione: (2025)

Breaking the curse of dimensionality for linear rules: optimal predictors over the ellipsoid
di: Ayme, Alexis, et al.
Pubblicazione: (2025)

Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristics
di: Liu, Hongyu, et al.
Pubblicazione: (2024)

Multi-objective Optimization by Learning Space Partitions
di: Zhao, Yiyang, et al.
Pubblicazione: (2021)

Omnipresent Yet Overlooked: Heat Kernels in Combinatorial Bayesian Optimization
di: Doumont, Colin, et al.
Pubblicazione: (2025)

FreeMOCA: Memory-Free Continual Learning for Malicious Code Analysis
di: Asadi, Zahra, et al.
Pubblicazione: (2026)

DeeP-Mod: Deep Dynamic Programming based Environment Modelling using Feature Extraction
di: Child, Chris, et al.
Pubblicazione: (2025)

Molecular Representations in Implicit Functional Space via Hyper-Networks
di: Wang, Zehong, et al.
Pubblicazione: (2026)

Unsupervised Diffusion Solver for Combinatorial Optimization via Combinatorial Adjoint Matching
di: Feng, Shengyu, et al.
Pubblicazione: (2026)

MetaLLMix : An XAI Aided LLM-Meta-learning Based Approach for Hyper-parameters Optimization
di: Bal-Ghaoui, Mohamed, et al.
Pubblicazione: (2025)

HiBBO: HiPPO-based Space Consistency for High-dimensional Bayesian Optimisation
di: Xuan, Junyu, et al.
Pubblicazione: (2025)

Learn to Explore: Meta NAS via Bayesian Optimization Guided Graph Generation
di: Sun, Zijun, et al.
Pubblicazione: (2025)

Learning minimal volume uncertainty ellipsoids
di: Alon, Itai, et al.
Pubblicazione: (2024)

BOPO: Neural Combinatorial Optimization via Best-anchored and Objective-guided Preference Optimization
di: Liao, Zijun, et al.
Pubblicazione: (2025)

An Adaptive Dimension Reduction Estimation Method for High-dimensional Bayesian Optimization
di: Hu, Shouri, et al.
Pubblicazione: (2024)

Combinatorial Optimization with Policy Adaptation using Latent Space Search
di: Chalumeau, Felix, et al.
Pubblicazione: (2023)

Directed Evolution of Proteins via Bayesian Optimization in Embedding Space
di: Soldát, Matouš, et al.
Pubblicazione: (2025)

Navigating in High-Dimensional Search Space: A Hierarchical Bayesian Optimization Approach
di: Li, Wenxuan, et al.
Pubblicazione: (2024)

Training Feedforward Neural Networks with Bayesian Hyper-Heuristics
di: Schreuder, Arné, et al.
Pubblicazione: (2023)

A Meta-Level Learning Algorithm for Sequential Hyper-Parameter Space Reduction in AutoML
di: Borboudakis, Giorgos, et al.
Pubblicazione: (2023)

HyReaL: Clustering Attributed Graph via Hyper-Complex Space Representation Learning
di: Chen, Junyang, et al.
Pubblicazione: (2024)

Adversarial Query Synthesis via Bayesian Optimization
di: Tao, Jeffrey, et al.
Pubblicazione: (2026)

Improving LLM-based Global Optimization with Search Space Partitioning
di: Schwanke, Andrej, et al.
Pubblicazione: (2025)

Clustering-based Meta Bayesian Optimization with Theoretical Guarantee
di: Nguyen, Khoa, et al.
Pubblicazione: (2025)

MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
di: Pan, Jiarong, et al.
Pubblicazione: (2023)

Preference Optimization for Combinatorial Optimization Problems
di: Pan, Mingjun, et al.
Pubblicazione: (2025)