Copertina

Hyperparameter Optimization as a Service on INFN Cloud

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Barbetti, Matteo, Anderlini, Lucio
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Distributed, Parallel, and Cluster Computing Machine Learning Data Analysis, Statistics and Probability
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Supporting the development of Machine Learning for fundamental science in a federated Cloud with the AI_INFN platform
di: Anderlini, Lucio, et al.
Pubblicazione: (2025)

Real-Time XFEL Data Analysis at SLAC and NERSC: a Trial Run of Nascent Exascale Experimental Data Analysis
di: Blaschke, Johannes P., et al.
Pubblicazione: (2021)

Modeling Performance of Data Collection Systems for High-Energy Physics
di: Olin-Ammentorp, Wilkie, et al.
Pubblicazione: (2024)

An Active Learning-Based Streaming Pipeline for Reduced Data Training of Structure Finding Models in Neutron Diffractometry
di: Wang, Tianle, et al.
Pubblicazione: (2025)

The AI_INFN Platform: Artificial Intelligence Development in the Cloud
di: Anderlini, Lucio, et al.
Pubblicazione: (2025)

Track Lab: extensible data acquisition software for fast pixel detectors, online analysis and automation
di: Mánek, Petr, et al.
Pubblicazione: (2023)

Theoretical Analysis on Block Time Distributions in Byzantine Fault-Tolerant Consensus Blockchains
di: Fujihara, Akihiro
Pubblicazione: (2024)

SETI@home: Data Acquisition and Front-End Processing
di: Korpela, Eric J., et al.
Pubblicazione: (2025)

Real-Time Analysis of Unstructured Data with Machine Learning on Heterogeneous Architectures
di: Giasemis, Fotis I.
Pubblicazione: (2025)

SubMIT: A Physics Analysis Facility at MIT
di: Bendavid, Josh, et al.
Pubblicazione: (2025)

PASS: An Asynchronous Probabilistic Processor for Next Generation Intelligence
di: Patel, Saavan, et al.
Pubblicazione: (2024)

Sampling on Metric Graphs
di: Dwaraknath, Rajat Vadiraj, et al.
Pubblicazione: (2025)

Parallel Sampling via Autospeculation
di: Anari, Nima, et al.
Pubblicazione: (2025)

A Bayesian Optimization through Sequential Monte Carlo and Statistical Physics-Inspired Techniques
di: Lebedev, Anton, et al.
Pubblicazione: (2024)

Resource-Adaptive Successive Doubling for Hyperparameter Optimization with Large Datasets on High-Performance Computing Systems
di: Aach, Marcel, et al.
Pubblicazione: (2024)

Tuning the Tuner: Introducing Hyperparameter Optimization for Auto-Tuning
di: Willemsen, Floris-Jan, et al.
Pubblicazione: (2025)

Hotspot-Aware Scheduling of Virtual Machines with Overcommitment for Ultimate Utilization in Cloud Datacenters
di: Wu, Jiaxi, et al.
Pubblicazione: (2026)

A Holistic Framework for Automated Configuration Recommendation for Cloud Service Monitoring
di: Bastos, Anson, et al.
Pubblicazione: (2026)

MAIZX: A Carbon-Aware Framework for Optimizing Cloud Computing Emissions
di: Ruilova, Federico, et al.
Pubblicazione: (2025)

Long-term balanced allocation via thinning
di: Feldheim, Ohad N., et al.
Pubblicazione: (2021)

On the Locality of the Lovász Local Lemma
di: Davies-Peck, Peter
Pubblicazione: (2025)

Balls and Bins and the Infinite Process with Random Deletions
di: Berenbrink, Petra, et al.
Pubblicazione: (2025)

Decentralized Online Learning for Random Inverse Problems Over Graphs
di: Zhang, Xiwei, et al.
Pubblicazione: (2023)

Parallel Simulation for Log-concave Sampling and Score-based Diffusion Models
di: Zhou, Huanjian, et al.
Pubblicazione: (2024)

The Geometry of Fixed-Magnetization Spin Systems at Low Temperature
di: Calvert, Jacob, et al.
Pubblicazione: (2024)

FedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud Systems
di: Nguyen, Van-Dinh, et al.
Pubblicazione: (2021)

Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees
di: Yu, Xin, et al.
Pubblicazione: (2024)

SERFLOW: A Cross-Service Cost Optimization Framework for SLO-Aware Dynamic ML Inference
di: Zhang, Zongshun, et al.
Pubblicazione: (2025)

Contention Resolution, With and Without a Global Clock
di: Cai, Zixi, et al.
Pubblicazione: (2026)

The Time to Consensus in a Blockchain: Insights into Bitcoin's "6 Blocks Rule''
di: Dey, Partha S., et al.
Pubblicazione: (2025)

Governing Cloud Data Pipelines with Agentic AI
di: Kirubakaran, Aswathnarayan Muthukrishnan, et al.
Pubblicazione: (2025)

Improvements & Evaluations on the MLCommons CloudMask Benchmark
di: Chennamsetti, Varshitha, et al.
Pubblicazione: (2024)

FedPop: Federated Population-based Hyperparameter Tuning
di: Chen, Haokun, et al.
Pubblicazione: (2023)

Dependency Aware Incident Linking in Large Cloud Systems
di: Ghosh, Supriyo, et al.
Pubblicazione: (2024)

Synthetic Time Series for Anomaly Detection in Cloud Microservices
di: Allam, Mohamed, et al.
Pubblicazione: (2024)

Distributed computing for physics-based data-driven reduced modeling at scale: Application to a rotating detonation rocket engine
di: Farcas, Ionut-Gabriel, et al.
Pubblicazione: (2024)

TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression
di: He, Zelin, et al.
Pubblicazione: (2024)

Federated Learning Framework for Scalable AI in Heterogeneous HPC and Cloud Environments
di: Ghimire, Sangam, et al.
Pubblicazione: (2025)

(Almost) Perfect Discrete Iterative Load Balancing
di: Berenbrink, Petra, et al.
Pubblicazione: (2025)

Threshold-Driven Streaming Graph: Expansion and Rumor Spreading
di: Angileri, Flora, et al.
Pubblicazione: (2025)