Image de couverture de livre

SOCRATES: Simulation Optimization with Correlated Replicas and Adaptive Trajectory Evaluations

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Haoting, Chen, Haoxian, Zhan, Donglin, Zhao, Hanyang, Lam, Henry, Tang, Wenpin, Yao, David, Zheng, Zeyu
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

MallowsPO: Fine-Tune Your LLM with Preference Dispersions
par: Chen, Haoxian, et autres
Publié: (2024)

Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning
par: Zhao, Hanyang, et autres
Publié: (2024)

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning
par: Zhao, Hanyang, et autres
Publié: (2025)

Understanding Sampler Stochasticity in Training Diffusion Models for RLHF
par: Sheng, Jiayuan, et autres
Publié: (2025)

OPD+: Rethinking the Advantage Design for On-Policy Distillation
par: Zhao, Hanyang, et autres
Publié: (2026)

Collaborative Bayesian Optimization via Wasserstein Barycenters
par: Zhan, Donglin, et autres
Publié: (2025)

Contractive Diffusion Probabilistic Models
par: Tang, Wenpin, et autres
Publié: (2024)

Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial
par: Tang, Wenpin, et autres
Publié: (2024)

Pseudo-Bayesian Optimization
par: Chen, Haoxian, et autres
Publié: (2023)

RPO: Fine-Tuning Visual Generative Models via Rich Vision-Language Preferences
par: Zhao, Hanyang, et autres
Publié: (2025)

Language Model Prompt Selection via Simulation Optimization
par: Zhang, Haoting, et autres
Publié: (2024)

DiFFPO: Training Diffusion LLMs to Reason Fast and Furious via Reinforcement Learning
par: Zhao, Hanyang, et autres
Publié: (2025)

Daily Physical Activity Monitoring -- Adaptive Learning from Multi-source Motion Sensor Data
par: Zhang, Haoting, et autres
Publié: (2024)

Preference Tuning with Human Feedback on Language, Speech, and Vision Tasks: A Survey
par: Winata, Genta Indra, et autres
Publié: (2024)

Fine-tuning of diffusion models via stochastic control: entropy regularization and beyond
par: Tang, Wenpin, et autres
Publié: (2024)

Diffusion Generative Models Meet Compressed Sensing, with Applications to Imaging and Finance
par: Guo, Zhengyi, et autres
Publié: (2025)

Regret of exploratory policy improvement and $q$-learning
par: Tang, Wenpin, et autres
Publié: (2024)

RainbowPO: A Unified Framework for Combining Improvements in Preference Optimization
par: Zhao, Hanyang, et autres
Publié: (2024)

Generative Replica-Exchange: A Flow-based Framework for Accelerating Replica Exchange Simulations
par: Huang, Shengjie, et autres
Publié: (2026)

The Trap of Trajectory: Towards Understanding and Mitigating Spurious Correlations in Agentic Memory
par: Tang, Luoxi, et autres
Publié: (2026)

Data-Efficient and Robust Task Selection for Meta-Learning
par: Zhan, Donglin, et autres
Publié: (2024)

Spatial Conformal Inference through Localized Quantile Regression
par: Jiang, Hanyang, et autres
Publié: (2024)

LLM-Assisted Logic Rule Learning: Scaling Human Expertise for Time Series Anomaly Detection
par: Zhang, Haoting, et autres
Publié: (2026)

Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective
par: Elmachtoub, Adam N., et autres
Publié: (2023)

Conformal prediction for multi-dimensional time series by ellipsoidal sets
par: Xu, Chen, et autres
Publié: (2024)

Tweedie's Formulae and Diffusion Generative Models Beyond Gaussian
par: Tang, Wenpin, et autres
Publié: (2026)

Selecting the Best Optimizing System
par: Si, Nian, et autres
Publié: (2022)

Polynomial Voting Rules
par: Tang, Wenpin, et autres
Publié: (2022)

ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule
par: Huang, Yilie, et autres
Publié: (2026)

Variational Trajectory Optimization of Anisotropic Diffusion Schedules
par: Liu, Pengxi, et autres
Publié: (2026)

From Invariant Representations to Invariant Data: Provable Robustness to Spurious Correlations via Noisy Counterfactual Matching
par: Bai, Ruqi, et autres
Publié: (2025)

Optimizer's Information Criterion: Dissecting and Correcting Bias in Data-Driven Optimization
par: Iyengar, Garud, et autres
Publié: (2023)

Enhancing Kubernetes Automated Scheduling with Deep Learning and Reinforcement Techniques for Large-Scale Cloud Computing Optimization
par: Xu, Zheng, et autres
Publié: (2024)

Improving Generalization of Speech Separation in Real-World Scenarios: Strategies in Simulation, Optimization, and Evaluation
par: Chen, Ke, et autres
Publié: (2024)

Spatio-Temporal Conformal Prediction for Power Outage Data
par: Jiang, Hanyang, et autres
Publié: (2024)

Gradient-based Trajectory Optimization with Parallelized Differentiable Traffic Simulation
par: Son, Sanghyun, et autres
Publié: (2024)

Bilevel Optimization of Agent Skills via Monte Carlo Tree Search
par: Huang, Chenyi, et autres
Publié: (2026)

ASTRO: Adaptive Stitching via Dynamics-Guided Trajectory Rollouts
par: Yu, Hang, et autres
Publié: (2025)

Dissecting the Impact of Model Misspecification in Data-driven Optimization
par: Elmachtoub, Adam N., et autres
Publié: (2025)

Iterative Feature Space Optimization through Incremental Adaptive Evaluation
par: Wu, Yanping, et autres
Publié: (2025)