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On the Understandability of Machine Learning Practices in Deep Learning and Reinforcement Learning Based Systems

https://doi.org/10.2139/ssrn.4777776
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Basics of Software Engineering Experimentation
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Reporting Experiments in Software Engineering
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Estimating the Assessment Difficulty of CVSS Environmental Metrics: An Experiment
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Experimentation in Software Engineering
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Transfer Learning in Deep Reinforcement Learning
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Do background colors improve program comprehension in the #ifdef hell?
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Robust Statistical Methods for Empirical Software Engineering
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Empirical software engineering experts on the use of students and professionals in experiments
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Measuring the accuracy of software vulnerability assessments: experiments with students and professionals
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Experimental methods: Between-subject and within-subject design
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On the Understandability of Language Constructs to Structure the State and Behavior in Abstract State Machine Specifications: A Controlled Experiment
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Using Students as Subjects—A Comparative Study of Students and Professionals in Lead-Time Impact Assessment
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Dominance statistics: Ordinal analyses to answer ordinal questions.
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Comparing several robust tests of stochastic equality with ordinally scaled variables and small to moderate sized samples.
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Biases of Success Rate Differences Shown in Binomial Effect Size Displays.
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A Test of Goodness of Fit
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Multiple Comparisons Among Means
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On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown
inferredcites →https://doi.org/10.1093/biomet/52.3-4.591openalex-extracted
An Analysis of Variance Test for Normality (Complete Samples)
inferredcites →https://doi.org/10.1109/csci51800.2020.00065openalex-extracted
A Concise Review of Transfer Learning
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An experiment on comparing textual vs. visual industrial methods for security risk assessment
inferredcites →https://doi.org/10.1109/esem.2011.25openalex-extracted
Experimental Analysis of Textual and Graphical Representations for Software Architecture Design
inferredcites →https://doi.org/10.1109/icse.2015.82openalex-extracted
Are Students Representatives of Professionals in Software Engineering Experiments?
inferredcites →https://doi.org/10.1109/quatic.2014.19openalex-extracted
Comparing Three Notations for Defining Scenario-Based Model Tests: A Controlled Experiment
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Transfer Learning in Deep Reinforcement Learning: A Survey
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On the Understandability of Temporal Properties Formalized in Linear Temporal Logic, Property Specification Patterns and Event Processing Language
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On the Understandability of MLOps System Architectures
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Software Architecture for ML-based Systems: What Exists and What Lies Ahead
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Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
inferredcites →https://doi.org/10.1145/1414004.1414055openalex-extracted
Using students as subjects - an empirical evaluation
inferredcites →https://doi.org/10.1145/3306608openalex-extracted
How Understandable Are Pattern-based Behavioral Constraints for Novice Software Designers?
inferredcites →https://doi.org/10.1145/3698038.3698553openalex-extracted
Inshrinkerator: Compressing Deep Learning Training Checkpoints via Dynamic Quantization
inferredcites →https://doi.org/10.1186/s40537-022-00652-wopenalex-extracted
Transfer learning: a friendly introduction
inferredcites →https://doi.org/10.1207/s15327906mbr3103_4openalex-extracted
Answering Ordinal Questions with Ordinal Data Using Ordinal Statistics
inferredcites →https://doi.org/10.2307/1170422openalex-extracted
Analyzing and Interpreting Significant MANOVAs
inferredcites →https://doi.org/10.4135/9781071812082.n627openalex-extracted
Teoria Statistica Delle Classi e Calcolo Delle Probabilità
inferredcites →https://doi.org/10.4135/9781412961288.n455openalex-extracted
Teoria Statistica Delle Classi e Calcolo Delle Probabilità
inferredcites →https://doi.org/10.48550/arxiv.1910.10683openalex-extracted
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
inferredcites →https://doi.org/10.48550/arxiv.2009.13003openalex-extracted
On Efficient Constructions of Checkpoints
inferredcites →https://doi.org/10.48550/arxiv.2211.12005openalex-extracted
Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors
inferredcites →https://doi.org/10.1037/0033-2909.114.3.494openalex-snapshot
Dominance statistics: Ordinal analyses to answer ordinal questions.
inferredcites →https://doi.org/10.2307/2283970openalex-snapshot
On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown
inferredcites →https://doi.org/10.3102/00346543052003340openalex-snapshot
Analyzing and Interpreting Significant MANOVAs
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