Gopinath Chennupati

73 papers A* 3A 4B 5C 6Misc 4Journal 32Unranked 18

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Regularization Through Reasoning: Systematic Improvements in Language Model Classification via Explanation-Enhanced Fine-Tuning. CoRR Vivswan Shah, Randy Cogill, Hanwei Yue, Gopinath Chennupati, Rinat Khaziev
2024	Misc	`conf`	Significant ASR Error Detection for Conversational Voice Assistants. ICASSP John Harvill, Rinat Khaziev, Scarlett Li, Randy Cogill, Lidan Wang, Gopinath Chennupati, Hari Thadakamalla
2023	B	`conf`	BB-ML: Basic Block Performance Prediction using Machine Learning Techniques. ICPADS Hamdy Abdelkhalik, Shamminuj Aktar, Yehia Arafa, Atanu Barai, Gopinath Chennupati, Nandakishore Santhi, Nishant Panda, Nirmal Prajapati, Nazmul Haque Turja, Stephan J. Eidenbenz, Abdel-Hameed A. Badawy
2023	J	`jnl`	Federated Representation Learning for Automatic Speech Recognition. CoRR Guruprasad V. Ramesh, Gopinath Chennupati, Milind Rao, Anit Kumar Sahu, Ariya Rastrow, Jasha Droppo
2023	Misc	`conf`	Federated Self-Learning with Weak Supervision for Speech Recognition. ICASSP Milind Rao, Gopinath Chennupati, Gautam Tiwari, Anit Kumar Sahu, Anirudh Raju, Ariya Rastrow, Jasha Droppo
2023	J	`jnl`	Federated Self-Learning with Weak Supervision for Speech Recognition. CoRR Milind Rao, Gopinath Chennupati, Gautam Tiwari, Anit Kumar Sahu, Anirudh Raju, Ariya Rastrow, Jasha Droppo
2023	J	`jnl`	General-purpose Unsupervised Cyber Anomaly Detection via Non-negative Tensor Factorization. DTRAP Maksim Ekin Eren, Juston S. Moore, Erik Skau, Elisabeth Moore, Manish Bhattarai, Gopinath Chennupati, Boian S. Alexandrov
2023	A	`conf`	Learning When to Trust Which Teacher for Weakly Supervised ASR. INTERSPEECH Aakriti Agrawal, Milind Rao, Anit Kumar Sahu, Gopinath Chennupati, Andreas Stolcke
2023	J	`jnl`	Learning When to Trust Which Teacher for Weakly Supervised ASR. CoRR Aakriti Agrawal, Milind Rao, Anit Kumar Sahu, Gopinath Chennupati, Andreas Stolcke
2022	J	`jnl`	BB-ML: Basic Block Performance Prediction using Machine Learning Techniques. CoRR Shamminuj Aktar, Hamdy Abdelkhalik, Nazmul Haque Turja, Yehia Arafa, Atanu Barai, Nishant Panda, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz, Abdel-Hameed A. Badawy
2022	J	`jnl`	Can Calibration Improve Sample Prioritization? CoRR Ganesh Tata, Gautham Krishna Gudur, Gopinath Chennupati, Mohammad Emtiyaz Khan
2022	A*	`conf`	ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale. KDD Gopinath Chennupati, Milind Rao, Gurpreet Chadha, Aaron Eakin, Anirudh Raju, Gautam Tiwari, Anit Kumar Sahu, Ariya Rastrow, Jasha Droppo, Andy Oberlin, Buddha Nandanoor, Prahalad Venkataramanan, Zheng Wu, Pankaj Sitpure
2022	J	`jnl`	ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale. CoRR Gopinath Chennupati, Milind Rao, Gurpreet Chadha, Aaron Eakin, Anirudh Raju, Gautam Tiwari, Anit Kumar Sahu, Ariya Rastrow, Jasha Droppo, Andy Oberlin, Buddha Nandanoor, Prahalad Venkataramanan, Zheng Wu, Pankaj Sitpure
2022	J	`jnl`	Improved Protein Decoy Selection via Non-Negative Matrix Factorization. IEEE ACM Trans. Comput. Biol. Bioinform. Nasrin Akhter, Kazi Lutful Kabir, Gopinath Chennupati, Raviteja Vangara, Boian S. Alexandrov, Hristo N. Djidjev, Amarda Shehu
2022	J	`jnl`	PPT-Multicore: performance prediction of OpenMP applications using reuse profiles and analytical modeling. J. Supercomput. Atanu Barai, Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
2022	J	`jnl`	Quantum Algorithm Implementations for Beginners. ACM Trans. Quantum Comput. Abhijith Jayakumar, Adetokunbo Adedoyin, John Ambrosiano, Petr M. Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo N. Djidjev, David Gunter, Satish Karra, Nathan Lemons, Shizeng Lin, Alexander Malyzhenkov, David Mascarenas, Susan M. Mniszewski, Balu Nadiga, Daniel O'Malley, Diane Oyen, Scott Pakin, Lakshman Prasad, Randy Roberts, Phillip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter J. Swart, James G. Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu, Stephan J. Eidenbenz, Andreas Bärtschi, Patrick J. Coles, Marc Vuffray, Andrey Y. Lokhov
2021	C	`conf`	An Effective Baseline for Robustness to Distributional Shift. ICMLA Sunil Thulasidasan, Sushil Thapa, Sayera Dhaubhadel, Gopinath Chennupati, Tanmoy Bhattacharya, Jeff A. Bilmes
2021	J	`jnl`	An Effective Baseline for Robustness to Distributional Shift. CoRR Sunil Thulasidasan, Sushil Thapa, Sayera Dhaubhadel, Gopinath Chennupati, Tanmoy Bhattacharya, Jeff A. Bilmes
2021	J	`jnl`	Finding the Number of Latent Topics With Semantic Non-Negative Matrix Factorization. IEEE Access Raviteja Vangara, Manish Bhattarai, Erik Skau, Gopinath Chennupati, Hristo N. Djidjev, Thomas Tierney, James P. Smith, Valentin G. Stanev, Boian S. Alexandrov
2021	A	`conf`	Hybrid, scalable, trace-driven performance modeling of GPGPUs. SC Yehia Arafa, Abdel-Hameed A. Badawy, Ammar ElWazir, Atanu Barai, Ali Eker, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
2021	J	`jnl`	Machine Learning-enabled Scalable Performance Prediction of Scientific Codes. ACM Trans. Model. Comput. Simul. Gopinath Chennupati, Nandakishore Santhi, Phillip Romero, Stephan J. Eidenbenz
2021	J	`jnl`	PPT-Multicore: Performance Prediction of OpenMP applications using Reuse Profiles and Analytical Modeling. CoRR Atanu Barai, Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
2021	J	`jnl`	PPT-SASMM: Scalable Analytical Shared Memory Model: Predicting the Performance of Multicore Caches from a Single-Threaded Execution Trace. CoRR Atanu Barai, Gopinath Chennupati, Nandakishore Santhi, Abdel-Hameed A. Badawy, Yehia Arafa, Stephan J. Eidenbenz
2020	J	`jnl`	An Out of Memory tSVD for Big-Data Factorization. IEEE Access Hector Carrillo-Cabada, Erik Skau, Gopinath Chennupati, Boian S. Alexandrov, Hristo N. Djidjev
2020	J	`jnl`	Code Characterization With Graph Convolutions and Capsule Networks. IEEE Access Poornima Haridas, Gopinath Chennupati, Nandakishore Santhi, Phillip Romero, Stephan J. Eidenbenz
2020	J	`jnl`	Decoy Selection for Protein Structure Prediction Via Extreme Gradient Boosting and Ranking. CoRR Nasrin Akhter, Gopinath Chennupati, Hristo N. Djidjev, Amarda Shehu
2020	—	`conf`	Decoy Selection in Protein Structure Determination via Symmetric Non-negative Matrix Factorization. BIBM Kazi Lutful Kabir, Gopinath Chennupati, Raviteja Vangara, Hristo N. Djidjev, Boian S. Alexandrov, Amarda Shehu
2020	J	`jnl`	Decoy selection for protein structure prediction via extreme gradient boosting and ranking. BMC Bioinform. Nasrin Akhter, Gopinath Chennupati, Hristo N. Djidjev, Amarda Shehu
2020	—	`conf`	Distributed Non-Negative Tensor Train Decomposition. HPEC Manish Bhattarai, Gopinath Chennupati, Erik Skau, Raviteja Vangara, Hristo N. Djidjev, Boian S. Alexandrov
2020	J	`jnl`	Distributed Non-Negative Tensor Train Decomposition. CoRR Manish Bhattarai, Gopinath Chennupati, Erik Skau, Raviteja Vangara, Hristo N. Djidjev, Boian S. Alexandrov
2020	J	`jnl`	Distributed non-negative matrix factorization with determination of the number of latent features. J. Supercomput. Gopinath Chennupati, Raviteja Vangara, Erik Skau, Hristo N. Djidjev, Boian S. Alexandrov
2020	A	`conf`	Fast, accurate, and scalable memory modeling of GPGPUs using reuse profiles. ICS Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Atanu Barai, Nandakishore Santhi, Stephan J. Eidenbenz
2020	J	`jnl`	Machine Learning Enabled Scalable Performance Prediction of Scientific Codes. CoRR Gopinath Chennupati, Nandakishore Santhi, Phillip Romero, Stephan J. Eidenbenz
2020	B	`conf`	NVIDIA GPGPUs Instructions Energy Consumption. ISPASS Yehia Arafa, Ammar ElWazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz, Nandakishore Santhi
2020	—	`conf`	PPT-SASMM: Scalable Analytical Shared Memory Model: Predicting the Performance of Multicore Caches from a Single-Threaded Execution Trace. MEMSYS Atanu Barai, Gopinath Chennupati, Nandakishore Santhi, Abdel-Hameed A. Badawy, Yehia Arafa, Stephan J. Eidenbenz
2020	C	`conf`	Semantic Nonnegative Matrix Factorization with Automatic Model Determination for Topic Modeling. ICMLA Raviteja Vangara, Erik Skau, Gopinath Chennupati, Hristo N. Djidjev, Thomas Tierney, James P. Smith, Manish Bhattarai, Valentin G. Stanev, Boian S. Alexandrov
2020	J	`jnl`	Verified Instruction-Level Energy Consumption Measurement for NVIDIA GPUs. CoRR Yehia Arafa, Ammar ElWazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz, Nandakishore Santhi
2020	—	`conf`	Verified instruction-level energy consumption measurement for NVIDIA GPUs. CF Yehia Arafa, Ammar ElWazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz, Nandakishore Santhi
2020	J	`jnl`	Why I'm not Answering: Understanding Determinants of Classification of an Abstaining Classifier for Cancer Pathology Reports. CoRR Sayera Dhaubhadel, Jamaludin Mohd-Yusof, Kumkum Ganguly, Gopinath Chennupati, Sunil Thulasidasan, Nicolas W. Hengartner, Brent J. Mumphrey, Eric B. Durbin, Jennifer A. Doherty, Mireille Lemieux, Noah Schaefferkoetter, Georgia D. Tourassi, Linda Coyle, Lynne Penberthy, Benjamin McMahon, Tanmoy Bhattacharya
2019	J	`jnl`	Combating Label Noise in Deep Learning Using Abstention. CoRR Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff A. Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof
2019	A*	`conf`	Combating Label Noise in Deep Learning using Abstention. ICML Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff A. Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof
2019	C	`conf`	GPUs Cache Performance Estimation using Reuse Distance Analysis. IPCCC Yehia Arafa, Gopinath Chennupati, Atanu Barai, Abdel-Hameed A. Badawy, Nandakishore Santhi, Stephan J. Eidenbenz
2019	J	`jnl`	Instructions' Latencies Characterization for NVIDIA GPGPUs. CoRR Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
2019	—	`conf`	Low Overhead Instruction Latency Characterization for NVIDIA GPGPUs. HPEC Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
2019	J	`jnl`	Modeling Shared Cache Performance of OpenMP Programs using Reuse Distance. CoRR Atanu Barai, Gopinath Chennupati, Nandakishore Santhi, Abdel-Hameed A. Badawy, Stephan J. Eidenbenz
2019	—	`conf`	Non-Negative Matrix Factorization for Selection of Near-Native Protein Tertiary Structures. BIBM Nasrin Akhter, Raviteja Vangara, Gopinath Chennupati, Boian S. Alexandrov, Hristo N. Djidjev, Amarda Shehu
2019	A*	`conf`	On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks. NeurIPS Sunil Thulasidasan, Gopinath Chennupati, Jeff A. Bilmes, Tanmoy Bhattacharya, Sarah Michalak
2019	J	`jnl`	On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks. CoRR Sunil Thulasidasan, Gopinath Chennupati, Jeff A. Bilmes, Tanmoy Bhattacharya, Sarah Michalak
2019	—	`conf`	POSTER: GPUs Pipeline Latency Analysis. ASAP Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
2019	J	`jnl`	PPT-GPU: Scalable GPU Performance Modeling. IEEE Comput. Archit. Lett. Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
2019	—	`conf`	Scalable Performance Prediction of Codes with Memory Hierarchy and Pipelines. SIGSIM-PADS Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
2018	Misc	`conf`	Imcsim: Parameterized Performance Prediction for Implicit Monte Carlo codes. WSC Gopinath Chennupati, Stephan J. Eidenbenz, Alex Long, Olena Tkachenko, Joseph Zerr, Jason Liu
2018	—	`conf`	Improved Decoy Selection via Machine Learning and Ranking. ICCABS Nasrin Akhter, Gopinath Chennupati, Hristo N. Djidjev, Amarda Shehu
2018	—	`conf`	PPT-GPU: performance prediction toolkit for GPUs identifying the impact of caches: extended abstract. MEMSYS Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
2018	—	`conf`	Parallel Application Performance Prediction Using Analysis Based Models and HPC Simulations. SIGSIM-PADS Mohammad Abu Obaida, Jason Liu, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
2018	J	`jnl`	Quantum Algorithm Implementations for Beginners. CoRR Patrick J. Coles, Stephan J. Eidenbenz, Scott Pakin, Adetokunbo Adedoyin, John Ambrosiano, Petr M. Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo N. Djidjev, David Gunter, Satish Karra, Nathan Lemons, Shizeng Lin, Andrey Y. Lokhov, Alexander Malyzhenkov, David Mascarenas, Susan M. Mniszewski, Balu Nadiga, Dan O'Malley, Diane Oyen, Lakshman Prasad, Randy Roberts, Philip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter J. Swart, Marc Vuffray, Jim Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu
2018	—	`ch.`	Synthesis of Parallel Programs on Multi-Cores. Handbook of Grammatical Evolution Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan, Stephan J. Eidenbenz, Nandakishore Santhi
2017	C	`conf`	A Probabilistic Monte Carlo Framework for Branch Prediction. CLUSTER Bhargava Kalla, Nandakishore Santhi, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz
2017	—	`conf`	A Scalable Analytical Memory Model for CPU Performance Prediction. PMBS@SC Gopinath Chennupati, Nandakishore Santhi, Robert F. Bird, Sunil Thulasidasan, Abdel-Hameed A. Badawy, Satyajayant Misra, Stephan J. Eidenbenz
2017	C	`conf`	AMM: Scalable Memory Reuse Model to Predict the Performance of Physics Codes. CLUSTER Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz, Sunil Thulasidasan
2017	Misc	`conf`	An analytical memory hierarchy model for performance prediction. WSC Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz, Sunil Thulasidasan
2017	C	`conf`	Probabilistic Monte Carlo simulations for static branch prediction. IPCCC Bhargava Kalla, Nandakishore Santhi, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz
2016	B	`conf`	Automatic lock-free parallel programming on multi-core processors. CEC Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan
2015	B	`conf`	Automatic Evolution of Parallel Recursive Programs. EuroGP Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan
2015	B	`conf`	Automatic Evolution of Parallel Sorting Programs on Multi-cores. EvoApplications Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan
2015	—	`conf`	On the Automatic Generation of Efficient Parallel Iterative Sorting Algorithms. GECCO (Companion) Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan
2015	A	`conf`	Performance Optimization of Multi-Core Grammatical Evolution Generated Parallel Recursive Programs. GECCO Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan
2015	—	`conf`	Synthesis of Parallel Iterative Sorts with Multi-Core Grammatical Evolution. GECCO (Companion) Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan
2014	—	`conf`	Multi-core GE: automatic evolution of CPU based multi-core parallel programs. GECCO (Companion) Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan
2014	—	`conf`	On the efficiency of Multi-core Grammatical Evolution (MCGE) evolving multi-core parallel programs. NaBIC Gopinath Chennupati, Jeannie Fitzgerald, Conor Ryan
2014	—	`conf`	Predict the performance of GE with an ACO based machine learning algorithm. GECCO (Companion) Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan
2014	—	`conf`	Predict the success or failure of an evolutionary algorithm run. GECCO (Companion) Gopinath Chennupati, Conor Ryan, R. Muhammad Atif Azad
2014	J	`jnl`	eAnt-Miner : An Ensemble Ant-Miner to Improve the ACO Classification. CoRR Gopinath Chennupati