Rahul Yedida - RankMe

30 papers A* 1A 1B 1Journal 25Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Is Hyper-Parameter Optimization Different for Software Analytics? IEEE Trans. Software Eng. Rahul Yedida, Tim Menzies
2025	J	`jnl`	Radon-Nikodým Derivative: Re-imagining Anomaly Detection from a Measure Theoretic Perspective. CoRR Shlok Mehendale, Aditya Challa, Rahul Yedida, Sravan Danda, Santonu Sarkar, Snehanshu Saha
2025	J	`jnl`	Report from the ASE 2024 Workshop on Replications and Negative Results. ACM SIGSOFT Softw. Eng. Notes Rahul Yedida, Tim Menzies
2024	J	`jnl`	SMOOTHIE: A Theory of Hyper-parameter Optimization for Software Analytics. CoRR Rahul Yedida, Tim Menzies
2024	J	`jnl`	Strong convexity-guided hyper-parameter optimization for flatter losses. CoRR Rahul Yedida, Snehanshu Saha
2023	J	`jnl`	(Re)Use of Research Results (Is Rampant). Commun. ACM Maria Teresa Baldassarre, Neil A. Ernst, Ben Hermann, Tim Menzies, Rahul Yedida
2023	J	`jnl`	An expert system for redesigning software for cloud applications. Expert Syst. Appl. Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic
2023	J	`jnl`	How to Find Actionable Static Analysis Warnings: A Case Study With FindBugs. IEEE Trans. Software Eng. Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies
2022	J	`jnl`	How to Find Actionable Static Analysis Warnings. CoRR Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies
2022	A	`conf`	How to Improve Deep Learning for Software Analytics (a case study with code smell detection). MSR Rahul Yedida, Tim Menzies
2022	J	`jnl`	How to Improve Deep Learning for Software Analytics (a case study with code smell detection). CoRR Rahul Yedida, Tim Menzies
2022	J	`jnl`	On the Value of Oversampling for Deep Learning in Software Defect Prediction. IEEE Trans. Software Eng. Rahul Yedida, Tim Menzies
2022	J	`jnl`	Simpler Hyperparameter Optimization for Software Analytics: Why, How, When? IEEE Trans. Software Eng. Amritanshu Agrawal, Xueqi Yang, Rishabh Agrawal, Rahul Yedida, Xipeng Shen, Tim Menzies
2021	J	`jnl`	Crowdsourcing the State of the Art(ifacts). CoRR Maria Teresa Baldassarre, Neil A. Ernst, Ben Hermann, Tim Menzies, Rahul Yedida
2021	—	`conf`	Documenting evidence of a reuse of 'a systematic study of the class imbalance problem in convolutional neural networks'. ESEC/SIGSOFT FSE Rahul Yedida, Tim Menzies
2021	—	`conf`	Documenting evidence of a reuse of 'on the number of linear regions of deep neural networks'. ESEC/SIGSOFT FSE Rahul Yedida, Tim Menzies
2021	J	`jnl`	Learning to recognize actionable static code warnings (is intrinsically easy). Empir. Softw. Eng. Xueqi Yang, Jianfeng Chen, Rahul Yedida, Zhe Yu, Tim Menzies
2021	A*	`conf`	Lessons learned from hyper-parameter tuning for microservice candidate identification. ASE Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic
2021	J	`jnl`	Lessons learned from hyper-parameter tuning for microservice candidate identification. CoRR Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic
2021	J	`jnl`	LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence. Appl. Intell. Rahul Yedida, Snehanshu Saha, Tejas Prashanth
2021	J	`jnl`	Partitioning Cloud-based Microservices (via Deep Learning). CoRR Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic
2021	J	`jnl`	When SIMPLE is better than complex: A case study on deep learning for predicting Bugzilla issue close time. CoRR Rahul Yedida, Xueqi Yang, Tim Menzies
2020	J	`jnl`	How to Recognize Actionable Static Code Warnings (Using Linear SVMs). CoRR Xueqi Yang, Jianfeng Chen, Rahul Yedida, Zhe Yu, Tim Menzies
2020	J	`jnl`	Improving Deep Learning for Defect Prediction (using the GHOST Hyperparameter Optimizer). CoRR Rahul Yedida, Tim Menzies
2020	B	`conf`	Parsimonious Computing: A Minority Training Regime for Effective Prediction in Large Microarray Expression Data Sets. IJCNN Shailesh Sridhar, Snehanshu Saha, Azhar Shaikh, Rahul Yedida, Sriparna Saha
2020	J	`jnl`	Parsimonious Computing: A Minority Training Regime for Effective Prediction in Large Microarray Expression Data Sets. CoRR Shailesh Sridhar, Snehanshu Saha, Azhar Shaikh, Rahul Yedida, Sriparna Saha
2020	J	`jnl`	Text Mining to Identify and Extract Novel Disease Treatments From Unstructured Datasets. CoRR Rahul Yedida, Saad Mohammad Abrar, Cleber C. Melo-Filho, Eugene N. Muratov, Rada Chirkova, Alexander Tropsha
2019	J	`jnl`	A novel adaptive learning rate scheduler for deep neural networks. CoRR Rahul Yedida, Snehanshu Saha
2019	J	`jnl`	Evolution of Novel Activation Functions in Neural Network Training with Applications to Classification of Exoplanets. CoRR Snehanshu Saha, Nithin Nagaraj, Archana Mathur, Rahul Yedida
2018	J	`jnl`	Employee Attrition Prediction. CoRR Rahul Yedida, Rahul Reddy, Rakshit Vahi, Rahul Jana, Abhilash G. V., Deepti Kulkarni