Image de couverture de livre

MESS+: Energy-Optimal Inferencing in Language Model Zoos with Service Level Guarantees

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Ryan, Woisetschläger, Herbert, Wang, Shiqiang, Jacobsen, Hans Arno
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Systems and Control
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

MESS+: Dynamically Learned Inference-Time LLM Routing in Model Zoos with Service Level Guarantees
par: Woisetschläger, Herbert, et autres
Publié: (2025)

Position: Let's Develop Data Probes to Fundamentally Understand How Data Affects LLM Performance
par: Wang, Shiqiang, et autres
Publié: (2026)

Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining
par: Sow, Daouda, et autres
Publié: (2025)

MAR-FL: A Communication Efficient Peer-to-Peer Federated Learning System
par: Mulitze, Felix, et autres
Publié: (2025)

A Survey on Efficient Federated Learning Methods for Foundation Model Training
par: Woisetschläger, Herbert, et autres
Publié: (2024)

FLEdge: Benchmarking Federated Machine Learning Applications in Edge Computing Systems
par: Woisetschläger, Herbert, et autres
Publié: (2023)

Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly
par: Woisetschläger, Herbert, et autres
Publié: (2023)

SIGN: Schema-Induced Games for Naming
par: Zhang, Ryan, et autres
Publié: (2025)

An Efficient Learning-Based Solver for Two-Stage DC Optimal Power Flow with Feasibility Guarantees
par: Zhang, Ling, et autres
Publié: (2023)

Tangential Randomization in Linear Bandits (TRAiL): Guaranteed Inference and Regret Bounds
par: Güçlü, Arda, et autres
Publié: (2024)

Learning-Based Optimal Control with Performance Guarantees for Unknown Systems with Latent States
par: Lefringhausen, Robert, et autres
Publié: (2023)

ECO: Energy-Constrained Operator Learning for Chaotic Dynamics with Boundedness Guarantees
par: Goertzen, Andrea, et autres
Publié: (2025)

Transformer-like Inference from Optimal Control
par: Kudre, Aditya, et autres
Publié: (2026)

Deep Adaptive Model-Based Design of Experiments
par: Strouwen, Arno, et autres
Publié: (2026)

Stochastic Reinforcement Learning with Stability Guarantees for Control of Unknown Nonlinear Systems
par: Quartz, Thanin, et autres
Publié: (2024)

AOLO: Analysis and Optimization For Low-Carbon Oriented Wireless Large Language Model Services
par: Wang, Xiaoqi, et autres
Publié: (2025)

Global Performance Guarantees for Neural Network Models of AC Power Flow
par: Chevalier, Samuel, et autres
Publié: (2022)

Data-Driven Reachability Analysis via Diffusion Models with PAC Guarantees
par: Huang, Yanliang, et autres
Publié: (2026)

ReLU Networks for Model Predictive Control: Network Complexity and Performance Guarantees
par: Li, Xingchen, et autres
Publié: (2026)

Deep Reinforcement Learning-driven Cross-Community Energy Interaction Optimal Scheduling
par: Li, Yang, et autres
Publié: (2023)

Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach
par: Pan, Huazi, et autres
Publié: (2025)

Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems
par: Li, Haoyu, et autres
Publié: (2025)

Negative Imaginary Neural ODEs: Learning to Control Mechanical Systems with Stability Guarantees
par: Shi, Kanghong, et autres
Publié: (2025)

RE-LLM: Integrating Large Language Models into Renewable Energy Systems
par: Forootani, Ali, et autres
Publié: (2025)

Semi-Gradient SARSA Routing with Theoretical Guarantee on Traffic Stability and Weight Convergence
par: Wu, Yidan, et autres
Publié: (2025)

An Analysis of Safety Guarantees in Multi-Task Bayesian Optimization
par: Luebsen, Jannis O., et autres
Publié: (2025)

Temporal-Aware Deep Reinforcement Learning for Energy Storage Bidding in Energy and Contingency Reserve Markets
par: Li, Jinhao, et autres
Publié: (2024)

Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples
par: Zhang, Thomas T., et autres
Publié: (2024)

Synthesizing Neural Network Controllers with Closed-Loop Dissipativity Guarantees
par: Junnarkar, Neelay, et autres
Publié: (2024)

Imitation Learning of MPC with Neural Networks: Error Guarantees and Sparsification
par: Alsmeier, Hendrik, et autres
Publié: (2025)

Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning
par: De Lellis, Francesco, et autres
Publié: (2023)

Efficient Stochastic Optimal Control through Approximate Bayesian Input Inference
par: Watson, Joe, et autres
Publié: (2021)

Learning to Admit Optimally in an $M/M/k/k+N$ Queueing System with Unknown Service Rate
par: Adler, Saghar, et autres
Publié: (2022)

Safe Guaranteed Exploration for Non-linear Systems
par: Prajapat, Manish, et autres
Publié: (2024)

Any-Time Regret-Guaranteed Algorithm for Control of Linear Quadratic Systems
par: Chekan, Jafar Abbaszadeh, et autres
Publié: (2024)

Multi-agent Multi-armed Bandits with Minimum Reward Guarantee Fairness
par: Manupriya, Piyushi, et autres
Publié: (2025)

Finite-Time Guarantees for Multi-Agent Combinatorial Bandits with Nonstationary Rewards
par: Adams, Katherine B., et autres
Publié: (2025)

Koopman Data-Driven Predictive Control with Robust Stability and Recursive Feasibility Guarantees
par: de Jong, Thomas, et autres
Publié: (2024)

Topology-Aware Graph Reinforcement Learning for Energy Storage Systems Optimal Dispatch in Distribution Networks
par: Gao, Shuyi, et autres
Publié: (2026)

Accounting for Optimal Control in the Sizing of Isolated Hybrid Renewable Energy Systems Using Imitation Learning
par: Halvdansson, Simon, et autres
Publié: (2026)