Gopinath Chennupati
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
28
Venues
16
Active years
2014–2024
Best venue rank
A*
Where they publish
Papers
28 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | ICASSP | Significant ASR Error Detection for Conversational Voice Assistants. | John Harvill, Rinat Khaziev, Scarlett Li, Randy Cogill, Lidan Wang, Gopinath Chennupati, Hari Thadakamalla |
| 2023 | ICASSP | Federated Self-Learning with Weak Supervision for Speech Recognition. | Milind Rao, Gopinath Chennupati, Gautam Tiwari, Anit Kumar Sahu, Anirudh Raju, Ariya Rastrow, Jasha Droppo |
| 2023 | ICPADS | BB-ML: Basic Block Performance Prediction using Machine Learning Techniques. | 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 | Interspeech | Learning When to Trust Which Teacher for Weakly Supervised ASR. | Aakriti Agrawal, Milind Rao, Anit Kumar Sahu, Gopinath Chennupati, Andreas Stolcke |
| 2022 | KDD | ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale. | 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 |
| 2021 | ICMLA | An Effective Baseline for Robustness to Distributional Shift. | Sunil Thulasidasan, Sushil Thapa, Sayera Dhaubhadel, Gopinath Chennupati, Tanmoy Bhattacharya, Jeff A. Bilmes |
| 2021 | SC | Hybrid, scalable, trace-driven performance modeling of GPGPUs. | Yehia Arafa, Abdel-Hameed A. Badawy, Ammar ElWazir, Atanu Barai, Ali Eker, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz |
| 2020 | ICMLA | Semantic Nonnegative Matrix Factorization with Automatic Model Determination for Topic Modeling. | Raviteja Vangara, Erik Skau, Gopinath Chennupati, Hristo N. Djidjev, Thomas Tierney, James P. Smith, Manish Bhattarai, Valentin G. Stanev, Boian S. Alexandrov |
| 2020 | ICS | Fast, accurate, and scalable memory modeling of GPGPUs using reuse profiles. | Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Atanu Barai, Nandakishore Santhi, Stephan J. Eidenbenz |
| 2020 | ISPASS | NVIDIA GPGPUs Instructions Energy Consumption. | Yehia Arafa, Ammar ElWazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz, Nandakishore Santhi |
| 2019 | ICML | Combating Label Noise in Deep Learning using Abstention. | Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff A. Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof |
| 2019 | IPCCC | GPUs Cache Performance Estimation using Reuse Distance Analysis. | Yehia Arafa, Gopinath Chennupati, Atanu Barai, Abdel-Hameed A. Badawy, Nandakishore Santhi, Stephan J. Eidenbenz |
| 2019 | PADS | Scalable Performance Prediction of Codes with Memory Hierarchy and Pipelines. | Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz |
| 2018 | PADS | Parallel Application Performance Prediction Using Analysis Based Models and HPC Simulations. | Mohammad Abu Obaida, Jason Liu, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz |
| 2018 | WSC | Imcsim: Parameterized Performance Prediction for Implicit Monte Carlo codes. | Gopinath Chennupati, Stephan J. Eidenbenz, Alex Long, Olena Tkachenko, Joseph Zerr, Jason Liu |
| 2017 | CLUSTER | AMM: Scalable Memory Reuse Model to Predict the Performance of Physics Codes. | Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz, Sunil Thulasidasan |
| 2017 | CLUSTER | A Probabilistic Monte Carlo Framework for Branch Prediction. | Bhargava Kalla, Nandakishore Santhi, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz |
| 2017 | IPCCC | Probabilistic Monte Carlo simulations for static branch prediction. | Bhargava Kalla, Nandakishore Santhi, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz |
| 2017 | WSC | An analytical memory hierarchy model for performance prediction. | Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz, Sunil Thulasidasan |
| 2017 | SC | A Scalable Analytical Memory Model for CPU Performance Prediction. | Gopinath Chennupati, Nandakishore Santhi, Robert F. Bird, Sunil Thulasidasan, Abdel-Hameed A. Badawy, Satyajayant Misra, Stephan J. Eidenbenz |
| 2016 | CEC | Automatic lock-free parallel programming on multi-core processors. | Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan |
| 2015 | EUROGP | Automatic Evolution of Parallel Recursive Programs. | Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan |
| 2015 | GECCO | Performance Optimization of Multi-Core Grammatical Evolution Generated Parallel Recursive Programs. | Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan |
| 2015 | GECCO | Synthesis of Parallel Iterative Sorts with Multi-Core Grammatical Evolution. | Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan |
| 2015 | GECCO | On the Automatic Generation of Efficient Parallel Iterative Sorting Algorithms. | Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan |
| 2014 | GECCO | Multi-core GE: automatic evolution of CPU based multi-core parallel programs. | Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan |
| 2014 | GECCO | Predict the performance of GE with an ACO based machine learning algorithm. | Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan |
| 2014 | GECCO | Predict the success or failure of an evolutionary algorithm run. | Gopinath Chennupati, Conor Ryan, R. Muhammad Atif Azad |