Cover Image

On the Learnability of Offline Model-Based Optimization: A Ranking Perspective

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lyu, Shen-Huan, Tan, Rong-Xi, Xue, Ke, He, Yi-Xiao, Huang, Yu, Zhang, Qingfu, Qian, Chao
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Offline Model-Based Optimization by Learning to Rank
by: Tan, Rong-Xi, et al.
Published: (2024)

Offline Multi-Objective Optimization
by: Xue, Ke, et al.
Published: (2024)

Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
by: Tan, Rong-Xi, et al.
Published: (2025)

HELIX: Hybrid Encoding with Learnable Identity and Cross-dimensional Synthesis for Time Series Imputation
by: Zhang, Fengming, et al.
Published: (2026)

Enhancing Offline Model-Based RL via Active Model Selection: A Bayesian Optimization Perspective
by: Yang, Yu-Wei, et al.
Published: (2025)

Low Rank Learning for Offline Query Optimization
by: Yi, Zixuan, et al.
Published: (2025)

Breaking the Prototype Bias Loop: Confidence-Aware Federated Contrastive Learning for Highly Imbalanced Clients
by: Wu, Tian-Shuang, et al.
Published: (2026)

BBOPlace-Bench: Benchmarking Black-Box Optimization for Chip Placement
by: Xue, Ke, et al.
Published: (2025)

Beyond Token-level Supervision: Unlocking the Potential of Decoding-based Regression via Reinforcement Learning
by: Chen, Ming, et al.
Published: (2025)

Hypercube Policy Regularization Framework for Offline Reinforcement Learning
by: Shen, Yi, et al.
Published: (2024)

DiffCPS: Diffusion Model based Constrained Policy Search for Offline Reinforcement Learning
by: He, Longxiang, et al.
Published: (2023)

Robust Length Prediction: A Perspective from Heavy-Tailed Prompt-Conditioned Distributions
by: Wang, Jing, et al.
Published: (2026)

PMGDA: A Preference-based Multiple Gradient Descent Algorithm
by: Zhang, Xiaoyuan, et al.
Published: (2024)

Monte Carlo Tree Search based Space Transfer for Black-box Optimization
by: Wang, Shukuan, et al.
Published: (2024)

CoEvo: Continual Evolution of Symbolic Solutions Using Large Language Models
by: Guo, Ping, et al.
Published: (2024)

Model-Based Reinforcement Learning with Double Oracle Efficiency in Policy Optimization and Offline Estimation
by: Hu, Haichen, et al.
Published: (2026)

Grid-Mapping Pseudo-Count Constraint for Offline Reinforcement Learning
by: Shen, Yi, et al.
Published: (2024)

Neural Solver Selection for Combinatorial Optimization
by: Gao, Chengrui, et al.
Published: (2024)

FoMEMO: Towards Foundation Models for Expensive Multi-objective Optimization
by: Yao, Yiming, et al.
Published: (2025)

Offline Model-Based Optimization: Comprehensive Review
by: Kim, Minsu, et al.
Published: (2025)

Confidence-aware Contrastive Learning for Selective Classification
by: Wu, Yu-Chang, et al.
Published: (2024)

Diffusion Models as Optimizers for Efficient Planning in Offline RL
by: Huang, Renming, et al.
Published: (2024)

Quality-Diversity Optimization as Multi-Objective Optimization
by: Lin, Xi, et al.
Published: (2026)

Efficient Document Ranking with Learnable Late Interactions
by: Ji, Ziwei, et al.
Published: (2024)

Adaptive Coarse-to-Fine Subgoal Refinement for Long-Horizon Offline Goal-Conditioned Reinforcement Learning
by: Ke, Kaiqiang, et al.
Published: (2026)

Belief-Based Offline Reinforcement Learning for Delay-Robust Policy Optimization
by: Zhan, Simon Sinong, et al.
Published: (2025)

Unsupervised Data Generation for Offline Reinforcement Learning: A Perspective from Model
by: He, Shuncheng, et al.
Published: (2025)

Learning Design-Score Manifold to Guide Diffusion Models for Offline Optimization
by: Zhou, Tailin, et al.
Published: (2025)

Information-Theoretic Perspectives on Optimizers
by: Tan, Zhiquan, et al.
Published: (2025)

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization
by: Liu, Zongkai, et al.
Published: (2024)

From Function to Distribution Modeling: A PAC-Generative Approach to Offline Optimization
by: Zhang, Qiang, et al.
Published: (2024)

Policy-regularized Offline Multi-objective Reinforcement Learning
by: Lin, Qian, et al.
Published: (2024)

CoRA: Optimizing Low-Rank Adaptation with Common Subspace of Large Language Models
by: Xiao, Xiaojun, et al.
Published: (2024)

SUMO: Search-Based Uncertainty Estimation for Model-Based Offline Reinforcement Learning
by: Qiao, Zhongjian, et al.
Published: (2024)

Design Editing for Offline Model-based Optimization
by: Yuan, Ye, et al.
Published: (2024)

Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
by: Gao, Chen-Xiao, et al.
Published: (2025)

An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
by: Lin, Qian, et al.
Published: (2024)

CROP: Conservative Reward for Model-based Offline Policy Optimization
by: Li, Hao, et al.
Published: (2023)

Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?
by: Dai, Yang, et al.
Published: (2024)

Variational OOD State Correction for Offline Reinforcement Learning
by: Jiang, Ke, et al.
Published: (2025)