Employee Attrition Prediction. - Rahul Yedida; Rahul Reddy; Rakshit Vahi; Rahul Jana; Abhilash G. V.; Deepti Kulkarni (CoRR, 2018)

A novel adaptive learning rate scheduler for deep neural networks. - Rahul Yedida; Snehanshu Saha (CoRR, 2019)

Evolution of Novel Activation Functions in Neural Network Training with Applications to Classification of Exoplanets. - Snehanshu Saha; Nithin Nagaraj; Archana Mathur; Rahul Yedida (CoRR, 2019)

Parsimonious Computing: A Minority Training Regime for Effective Prediction in Large Microarray Expression Data Sets. - Shailesh Sridhar; Snehanshu Saha; Azhar Shaikh; Rahul Yedida; Sriparna Saha 001 (IJCNN, 2020)

How to Recognize Actionable Static Code Warnings (Using Linear SVMs). - Xueqi Yang; Jianfeng Chen; Rahul Yedida; Zhe Yu 002; Tim Menzies (CoRR, 2020)

Improving Deep Learning for Defect Prediction (using the GHOST Hyperparameter Optimizer). - Rahul Yedida; Tim Menzies (CoRR, 2020)

Text Mining to Identify and Extract Novel Disease Treatments From Unstructured Datasets. - Rahul Yedida; Saad Mohammad Abrar; Cleber C. Melo-Filho; Eugene N. Muratov; Rada Chirkova; Alexander Tropsha (CoRR, 2020)

Lessons learned from hyper-parameter tuning for microservice candidate identification. - Rahul Yedida; Rahul Krishna; Anup K. Kalia; Tim Menzies; Jin Xiao; Maja Vukovic (ASE, 2021)

Documenting evidence of a reuse of 'a systematic study of the class imbalance problem in convolutional neural networks'. - Rahul Yedida; Tim Menzies (ESEC/SIGSOFT FSE, 2021)

Documenting evidence of a reuse of 'on the number of linear regions of deep neural networks'. - Rahul Yedida; Tim Menzies (ESEC/SIGSOFT FSE, 2021)

LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence. - Rahul Yedida; Snehanshu Saha; Tejas Prashanth (Appl. Intell., 2021)

When SIMPLE is better than complex: A case study on deep learning for predicting Bugzilla issue close time. - Rahul Yedida; Xueqi Yang; Tim Menzies (CoRR, 2021)

Crowdsourcing the State of the Art(ifacts). - Maria Teresa Baldassarre; Neil A. Ernst; Ben Hermann; Tim Menzies; Rahul Yedida (CoRR, 2021)

Partitioning Cloud-based Microservices (via Deep Learning). - Rahul Yedida; Rahul Krishna; Anup K. Kalia; Tim Menzies; Jin Xiao; Maja Vukovic (CoRR, 2021)

Learning to recognize actionable static code warnings (is intrinsically easy). - Xueqi Yang; Jianfeng Chen; Rahul Yedida; Zhe Yu 002; Tim Menzies (Empir. Softw. Eng., 2021)

How to Improve Deep Learning for Software Analytics (a case study with code smell detection). - Rahul Yedida; Tim Menzies (MSR, 2022)

How to Find Actionable Static Analysis Warnings. - Rahul Yedida; Hong Jin Kang; Huy Tu; Xueqi Yang; David Lo 001; Tim Menzies (CoRR, 2022)

Simpler Hyperparameter Optimization for Software Analytics: Why, How, When? - Amritanshu Agrawal; Xueqi Yang; Rishabh Agrawal; Rahul Yedida; Xipeng Shen; Tim Menzies (IEEE Trans. Software Eng., 2022)

On the Value of Oversampling for Deep Learning in Software Defect Prediction. - Rahul Yedida; Tim Menzies (IEEE Trans. Software Eng., 2022)

(Re)Use of Research Results (Is Rampant). - Maria Teresa Baldassarre; Neil A. Ernst; Ben Hermann; Tim Menzies; Rahul Yedida (Commun. ACM, 2023)

How to Find Actionable Static Analysis Warnings: A Case Study With FindBugs. - Rahul Yedida; Hong Jin Kang; Huy Tu; Xueqi Yang; David Lo 001; Tim Menzies (IEEE Trans. Software Eng., 2023)

An expert system for redesigning software for cloud applications. - Rahul Yedida; Rahul Krishna; Anup K. Kalia; Tim Menzies; Jin Xiao; Maja Vukovic (Expert Syst. Appl., 2023)

SMOOTHIE: A Theory of Hyper-parameter Optimization for Software Analytics. - Rahul Yedida; Tim Menzies (CoRR, 2024)

Strong convexity-guided hyper-parameter optimization for flatter losses. - Rahul Yedida; Snehanshu Saha (CoRR, 2024)

Radon-Nikodým Derivative: Re-imagining Anomaly Detection from a Measure Theoretic Perspective. - Shlok Mehendale; Aditya Challa; Rahul Yedida; Sravan Danda; Santonu Sarkar; Snehanshu Saha (CoRR, 2025)

Is Hyper-Parameter Optimization Different for Software Analytics? - Rahul Yedida; Tim Menzies (IEEE Trans. Software Eng., 2025)

Report from the ASE 2024 Workshop on Replications and Negative Results. - Rahul Yedida; Tim Menzies (ACM SIGSOFT Softw. Eng. Notes, 2025)