arXiv (All)
open access
Scalable Distributed Learning-Based MPC for Heterogeneous Consumer-Prosumer Building Aggregations: MPC-Aware Feature Selection and Convex Constraint-Coupled Optimization
Buildings provide demand-response flexibility through controllable thermal loads and thermal inertia, while distributed photovoltaic deployment creates opportunities to share surplus generation across heterogeneous consumer-prosumer aggregations. This study develops a scalable distributed learning-b
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Coral: Cost-Efficient Multi-LLM Serving over Heterogeneous Cloud GPUs#168288
- DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures#792673
- DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures#788673
- Multi-scale hybrid composites of erythritol/diatomite/GNP for enhanced thermal energy storage: experimental and machine learning optimization.#209417
- Predictive Lightweight MARL for Resilient Coverage in Sparse-Signaling Aerial Networks#820567
Record · ID 1115550
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive