What makes a popular academic AI repository?
暂无分享,去创建一个
Xin Xia | Ahmed E. Hassan | Shanping Li | David Lo | Yuanrui Fan | Shanping Li | Xin Xia | David Lo | Yuanrui Fan
[1] Marco Tulio Valente,et al. Predicting the Popularity of GitHub Repositories , 2016, PROMISE.
[2] J. Fleiss. Measuring nominal scale agreement among many raters. , 1971 .
[3] Brian A. Nosek,et al. Promoting an open research culture , 2015, Science.
[4] David Lo,et al. Popularity, Interoperability, and Impact of Programming Languages in 100,000 Open Source Projects , 2013, 2013 IEEE 37th Annual Computer Software and Applications Conference.
[5] Julio Cesar Sampaio do Prado Leite,et al. Extracting Requirements Patterns from Software Repositories , 2016, 2016 IEEE 24th International Requirements Engineering Conference Workshops (REW).
[6] David W. Aha,et al. On Reproducible AI Towards reproducible research, open science, and digital scholarship in AI publications , 2019 .
[7] Lynne M Connelly,et al. Fisher's Exact Test. , 2016, Medsurg nursing : official journal of the Academy of Medical-Surgical Nurses.
[8] Miryung Kim,et al. An ethnographic study of copy and paste programming practices in OOPL , 2004, Proceedings. 2004 International Symposium on Empirical Software Engineering, 2004. ISESE '04..
[9] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[10] Audris Mockus,et al. Patterns of folder use and project popularity: a case study of github repositories , 2014, ESEM '14.
[11] Shane McIntosh,et al. Revisiting the Impact of Classification Techniques on the Performance of Defect Prediction Models , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[12] Ahmed E. Hassan,et al. An Experience Report on Defect Modelling in Practice: Pitfalls and Challenges , 2017, 2018 IEEE/ACM 40th International Conference on Software Engineering: Software Engineering in Practice Track (ICSE-SEIP).
[13] Zhuo Yang,et al. Influence analysis of Github repositories , 2016, SpringerPlus.
[14] Damminda Alahakoon,et al. Minority report in fraud detection: classification of skewed data , 2004, SKDD.
[15] Maria-Florina Balcan,et al. Learning to Branch , 2018, ICML.
[16] David Lo,et al. What are the characteristics of high-rated apps? A case study on free Android Applications , 2015, 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME).
[17] David Lo,et al. Automating Change-Level Self-Admitted Technical Debt Determination , 2019, IEEE Transactions on Software Engineering.
[18] David Lo,et al. Chaff from the Wheat: Characterizing and Determining Valid Bug Reports , 2020, IEEE Transactions on Software Engineering.
[19] Christoph Treude,et al. Categorizing the Content of GitHub README Files , 2018, Empirical Software Engineering.
[20] David Lo,et al. Why and how developers fork what from whom in GitHub , 2017, Empirical Software Engineering.
[21] Carl E. Rasmussen,et al. The Need for Open Source Software in Machine Learning , 2007, J. Mach. Learn. Res..
[22] Marco Tulio Valente,et al. Understanding the Factors That Impact the Popularity of GitHub Repositories , 2016, 2016 IEEE International Conference on Software Maintenance and Evolution (ICSME).
[23] Karl Fogel,et al. Producing open source software - how to run a successful free software project , 2005 .
[24] Jan Kautz,et al. Video-to-Video Synthesis , 2018, NeurIPS.
[25] Ling Xu,et al. Automating Aggregation for Software Quality Modeling , 2017, 2017 IEEE International Conference on Software Maintenance and Evolution (ICSME).
[26] Christa Boer,et al. Correlation Coefficients: Appropriate Use and Interpretation , 2018, Anesthesia and analgesia.
[27] J. Kimble. Plain English: A Charter for Clear Writing@ (Part Three) , 1992 .
[28] Rodney X. Sturdivant,et al. Applied Logistic Regression: Hosmer/Applied Logistic Regression , 2005 .
[29] David Lo,et al. Early prediction of merged code changes to prioritize reviewing tasks , 2018, Empirical Software Engineering.
[30] Frank E. Harrell,et al. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2001 .
[31] Christian S. Collberg,et al. Repeatability in computer systems research , 2016, Commun. ACM.
[32] Shuiguang Deng,et al. Characterization and Prediction of Popular Projects on GitHub , 2019, 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC).
[33] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[34] J. H. Zar,et al. Spearman Rank Correlation , 2005 .
[35] G. Upton. Fisher's Exact Test , 1992 .
[36] David Lo,et al. The Impact of Mislabeled Changes by SZZ on Just-in-Time Defect Prediction , 2019, IEEE Transactions on Software Engineering.
[37] Yuanyuan Zhou,et al. CP-Miner: finding copy-paste and related bugs in large-scale software code , 2006, IEEE Transactions on Software Engineering.
[38] Eleni Stroulia,et al. Co-evolution of project documentation and popularity within github , 2014, MSR 2014.
[39] Stefan Lee,et al. Graph R-CNN for Scene Graph Generation , 2018, ECCV.
[40] Tiago L. Alves,et al. Deriving metric thresholds from benchmark data , 2010, 2010 IEEE International Conference on Software Maintenance.
[41] Timothy Baldwin,et al. Automatic Evaluation of Topic Coherence , 2010, NAACL.
[42] Samy Bengio,et al. Torch: a modular machine learning software library , 2002 .
[43] Carl Boettiger,et al. An introduction to Docker for reproducible research , 2014, OPSR.
[44] Arie van Deursen,et al. An exploratory study of the pull-based software development model , 2014, ICSE.
[45] David Lo,et al. How Practitioners Perceive Coding Proficiency , 2019, 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE).
[46] Shane McIntosh,et al. An Empirical Comparison of Model Validation Techniques for Defect Prediction Models , 2017, IEEE Transactions on Software Engineering.
[47] David Lo,et al. Perceptions, Expectations, and Challenges in Defect Prediction , 2020, IEEE Transactions on Software Engineering.
[48] David Lo,et al. Mining Sandboxes for Linux Containers , 2017, 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST).
[49] N. Cliff. Ordinal methods for behavioral data analysis , 1996 .
[50] Shane McIntosh,et al. The Impact of Automated Parameter Optimization on Defect Prediction Models , 2018, IEEE Transactions on Software Engineering.
[51] A. Scott,et al. A Cluster Analysis Method for Grouping Means in the Analysis of Variance , 1974 .
[52] Jiebo Luo,et al. What Makes an Open Source Code Popular on Git Hub? , 2014, 2014 IEEE International Conference on Data Mining Workshop.
[53] Charles X. Ling,et al. Using AUC and accuracy in evaluating learning algorithms , 2005, IEEE Transactions on Knowledge and Data Engineering.
[54] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.
[55] Scott N. Woodfield,et al. The effect of modularization and comments on program comprehension , 1981, ICSE '81.
[56] F. Wilcoxon. Individual Comparisons by Ranking Methods , 1945 .
[57] Leo Breiman,et al. Random Forests , 2001, Machine Learning.