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Found 6 papers, 3 papers with code
Good Intentions: Adaptive Parameter Management via Intent Signaling
Parameter management is essential for distributed training of large machine learning (ML) tasks.
Towards Loosely-Coupling Knowledge Graph Embeddings and Ontology-based Reasoning
Knowledge graph completion (a. k. a.~link prediction), i. e.,~the task of inferring missing information from knowledge graphs, is a widely used task in many applications, such as product recommendation and question answering.
NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access
Parameter servers (PSs) facilitate the implementation of distributed training for large machine learning tasks.
RDFFrames: Knowledge Graph Access for Machine Learning Tools
Thus, RDFFrames is a useful tool for data preparation that combines the usability of PyData with the flexibility and performance of RDF database systems.
Agora: A Unified Asset Ecosystem Going Beyond Marketplaces and Cloud Services
Data, algorithms, and compute/storage infrastructure are key assets that drive data science and artificial intelligence applications.
AI-CARGO: A Data-Driven Air-Cargo Revenue Management System
The discrepancy results in sub-optimal and inefficient behavior by both the shipper and the airline resulting in the overall loss of potential revenue for the airline.
