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ORCIDRahul Yedida
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2020 – today
- 2024
[i15]Rahul Yedida, Tim Menzies:
SMOOTHIE: A Theory of Hyper-parameter Optimization for Software Analytics. CoRR abs/2401.09622 (2024)- [i14]Rahul Yedida, Snehanshu Saha:
Strong convexity-guided hyper-parameter optimization for flatter losses. CoRR abs/2402.05025 (2024) - 2023
- [j7]Maria Teresa Baldassarre, Neil A. Ernst, Ben Hermann
, Tim Menzies, Rahul Yedida:
(Re)Use of Research Results (Is Rampant). Commun. ACM 66(2): 75-81 (2023) - [j6]Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic:
An expert system for redesigning software for cloud applications. Expert Syst. Appl. 219: 119673 (2023) - [j5]Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies:
How to Find Actionable Static Analysis Warnings: A Case Study With FindBugs. IEEE Trans. Software Eng. 49(4): 2856-2872 (2023) - 2022
- [j4]Amritanshu Agrawal, Xueqi Yang, Rishabh Agrawal, Rahul Yedida, Xipeng Shen, Tim Menzies:
Simpler Hyperparameter Optimization for Software Analytics: Why, How, When? IEEE Trans. Software Eng. 48(8): 2939-2954 (2022) - [j3]Rahul Yedida, Tim Menzies:
On the Value of Oversampling for Deep Learning in Software Defect Prediction. IEEE Trans. Software Eng. 48(8): 3103-3116 (2022) - [c5]Rahul Yedida, Tim Menzies:
How to Improve Deep Learning for Software Analytics (a case study with code smell detection). MSR 2022: 156-166 - [i13]Rahul Yedida, Tim Menzies:
How to Improve Deep Learning for Software Analytics (a case study with code smell detection). CoRR abs/2202.01322 (2022) - [i12]Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies:
How to Find Actionable Static Analysis Warnings. CoRR abs/2205.10504 (2022) - 2021
- [j2]Rahul Yedida, Snehanshu Saha, Tejas Prashanth:
LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence. Appl. Intell. 51(3): 1460-1478 (2021) - [j1]Xueqi Yang, Jianfeng Chen, Rahul Yedida, Zhe Yu, Tim Menzies:
Learning to recognize actionable static code warnings (is intrinsically easy). Empir. Softw. Eng. 26(3): 56 (2021) - [c4]Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic:
Lessons learned from hyper-parameter tuning for microservice candidate identification. ASE 2021: 1141-1145 - [c3]Rahul Yedida, Tim Menzies:
Documenting evidence of a reuse of 'a systematic study of the class imbalance problem in convolutional neural networks'. ESEC/SIGSOFT FSE 2021: 1595 - [c2]Rahul Yedida, Tim Menzies:
Documenting evidence of a reuse of 'on the number of linear regions of deep neural networks'. ESEC/SIGSOFT FSE 2021: 1596 - [i11]Rahul Yedida, Xueqi Yang, Tim Menzies:
When SIMPLE is better than complex: A case study on deep learning for predicting Bugzilla issue close time. CoRR abs/2101.06319 (2021) - [i10]Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic:
Lessons learned from hyper-parameter tuning for microservice candidate identification. CoRR abs/2106.06652 (2021) - [i9]Maria Teresa Baldassarre, Neil A. Ernst, Ben Hermann, Tim Menzies, Rahul Yedida:
Crowdsourcing the State of the Art(ifacts). CoRR abs/2108.06821 (2021) - [i8]Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic:
Partitioning Cloud-based Microservices (via Deep Learning). CoRR abs/2109.14569 (2021) - 2020
- [c1]Shailesh Sridhar, Snehanshu Saha, Azhar Shaikh, Rahul Yedida, Sriparna Saha:
Parsimonious Computing: A Minority Training Regime for Effective Prediction in Large Microarray Expression Data Sets. IJCNN 2020: 1-8 - [i7]Shailesh Sridhar, Snehanshu Saha, Azhar Shaikh, Rahul Yedida, Sriparna Saha:
Parsimonious Computing: A Minority Training Regime for Effective Prediction in Large Microarray Expression Data Sets. CoRR abs/2005.08442 (2020) - [i6]Xueqi Yang, Jianfeng Chen, Rahul Yedida, Zhe Yu, Tim Menzies:
How to Recognize Actionable Static Code Warnings (Using Linear SVMs). CoRR abs/2006.00444 (2020) - [i5]Rahul Yedida, Tim Menzies:
Improving Deep Learning for Defect Prediction (using the GHOST Hyperparameter Optimizer). CoRR abs/2008.03835 (2020) - [i4]Rahul Yedida, Saad Mohammad Abrar, Cleber C. Melo-Filho, Eugene N. Muratov, Rada Chirkova, Alexander Tropsha:
Text Mining to Identify and Extract Novel Disease Treatments From Unstructured Datasets. CoRR abs/2011.07959 (2020)
2010 – 2019
- 2019
- [i3]Rahul Yedida, Snehanshu Saha:
A novel adaptive learning rate scheduler for deep neural networks. CoRR abs/1902.07399 (2019) - [i2]Snehanshu Saha, Nithin Nagaraj, Archana Mathur, Rahul Yedida:
Evolution of Novel Activation Functions in Neural Network Training with Applications to Classification of Exoplanets. CoRR abs/1906.01975 (2019) - 2018
- [i1]Rahul Yedida, Rahul Reddy, Rakshit Vahi, Rahul Jana, Abhilash G. V., Deepti Kulkarni:
Employee Attrition Prediction. CoRR abs/1806.10480 (2018)
Coauthor Index
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