On the public citation graph
FaaS Forecasting: Predicting Runtime & Cost with Machine Learning in Orama Framework
0 signed · 21 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-13342-9_15openalex-snapshot
FaaStest - Machine Learning Based Cost and Performance FaaS Optimization
inferredcites →https://doi.org/10.1007/978-3-031-84617-5_10openalex-snapshot
ML-Based Performance Modeling in Edge FaaS Systems
inferredcites →https://doi.org/10.1007/s00521-021-05916-9openalex-snapshot
BiLSTM regression model for face sketch synthesis using sequential patterns
inferredcites →https://doi.org/10.1007/s41965-019-00023-0openalex-snapshot
Hyperparameter optimization in learning systems
inferredcites →https://doi.org/10.1016/j.compbiomed.2024.108130openalex-snapshot
Bias reduction using combined stain normalization and augmentation for AI-based classification of histological images
inferredcites →https://doi.org/10.1016/j.eswa.2021.115293openalex-snapshot
A novel extreme learning machine based kNN classification method for dealing with big data
inferredcites →https://doi.org/10.1038/323533a0openalex-snapshot
Learning representations by back-propagating errors
inferredcites →https://doi.org/10.1080/02664763.2010.545119openalex-snapshot
Features and performance of some outlier detection methods
inferredcites →https://doi.org/10.1109/access.2018.2852759openalex-snapshot
Outlier Data Treatment Methods Toward Smart Grid Applications
inferredcites →https://doi.org/10.1109/icaisd63055.2024.10895942openalex-snapshot
Hyperparameter Tuning Optimization on Machine Learning Models to Predict Software Defects
inferredcites →https://doi.org/10.1109/qce60285.2024.00179openalex-snapshot
Quantum Machine Learning Architecture Search via Deep Reinforcement Learning
inferredcites →https://doi.org/10.1145/3406011openalex-snapshot
What serverless computing is and should become
inferredcites →https://doi.org/10.1145/3605098.3636033openalex-snapshot
FuncMem: Reducing Cold Start Latency in Serverless Computing Through Memory Prediction and Adaptive Task Execution
inferredcites →https://doi.org/10.18517/ijaseit.14.4.20191openalex-snapshot
Challenges in Supervised and Unsupervised Learning: A Comprehensive Overview
inferredcites →https://doi.org/10.3390/app142412037openalex-snapshot
Application of Machine Learning for Estimating the Physical Parameters of Three-Dimensional Fractures
inferredcites →https://doi.org/10.3390/e24070876openalex-snapshot
Densely Connected Neural Networks for Nonlinear Regression
inferredcites →https://doi.org/10.3390/smartcities4020029openalex-snapshot
Artificial Intelligence Techniques in Smart Grid: A Survey
inferredcites →https://doi.org/10.47738/ijiis.v4i1.73openalex-snapshot
Comparison of Min-Max normalization and Z-Score Normalization in the K-nearest neighbor (kNN) Algorithm to Test the Accuracy of Types of Breast Cancer
inferredcites →https://doi.org/10.7717/peerj-cs.1647openalex-snapshot
Evaluating the effectiveness of decomposed Halstead Metrics in software fault prediction
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.