Rahul Yedida

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 27

Top Topics

Adaptive Learning Rate

Defect Prediction

Top Venues

IEEE Trans. Software Eng.

ESEC/SIGSOFT FSE

Publications

Rahul Yedida, Tim Menzies
SMOOTHIE: A Theory of Hyper-parameter Optimization for Software Analytics. CoRR (2024)
Rahul Yedida, Snehanshu Saha
Strong convexity-guided hyper-parameter optimization for flatter losses. CoRR (2024)
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 (2023)
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) (2023)
Maria Teresa Baldassarre, Neil A. Ernst, Ben Hermann, Tim Menzies, Rahul Yedida
(Re)Use of Research Results (Is Rampant). Commun. ACM 66 (2) (2023)
Rahul Yedida, Tim Menzies
How to Improve Deep Learning for Software Analytics (a case study with code smell detection). MSR (2022)
Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies
How to Find Actionable Static Analysis Warnings. CoRR (2022)
Rahul Yedida, Tim Menzies
How to Improve Deep Learning for Software Analytics (a case study with code smell detection). CoRR (2022)
Rahul Yedida, Tim Menzies
On the Value of Oversampling for Deep Learning in Software Defect Prediction. IEEE Trans. Software Eng. 48 (8) (2022)
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) (2022)
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)
Maria Teresa Baldassarre, Neil A. Ernst, Ben Hermann, Tim Menzies, Rahul Yedida
Crowdsourcing the State of the Art(ifacts). CoRR (2021)
Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic
Lessons learned from hyper-parameter tuning for microservice candidate identification. CoRR (2021)
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) (2021)
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 (2021)
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)
Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic
Partitioning Cloud-based Microservices (via Deep Learning). CoRR (2021)
Rahul Yedida, Snehanshu Saha, Tejas Prashanth
LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence. Appl. Intell. 51 (3) (2021)
Rahul Yedida, Tim Menzies
Documenting evidence of a reuse of 'on the number of linear regions of deep neural networks'. ESEC/SIGSOFT FSE (2021)
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)
Rahul Yedida, Tim Menzies
Improving Deep Learning for Defect Prediction (using the GHOST Hyperparameter Optimizer). CoRR (2020)
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 (2020)
Xueqi Yang, Jianfeng Chen, Rahul Yedida, Zhe Yu, Tim Menzies
How to Recognize Actionable Static Code Warnings (Using Linear SVMs). CoRR (2020)
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 (2020)
Snehanshu Saha, Nithin Nagaraj, Archana Mathur, Rahul Yedida
Evolution of Novel Activation Functions in Neural Network Training with Applications to Classification of Exoplanets. CoRR (2019)
Rahul Yedida, Snehanshu Saha
A novel adaptive learning rate scheduler for deep neural networks. CoRR (2019)
Rahul Yedida, Rahul Reddy, Rakshit Vahi, Rahul Jana, Abhilash G. V., Deepti Kulkarni
Employee Attrition Prediction. CoRR (2018)