| Active federated learning J Goetz, K Malik, D Bui, S Moon, H Liu, A Kumar arXiv preprint arXiv:1909.12641, 2019 | 93 | 2019 |
| Federated learning with buffered asynchronous aggregation J Nguyen, K Malik, H Zhan, A Yousefpour, M Rabbat, M Malek, D Huba International Conference on Artificial Intelligence and Statistics, 3581-3607, 2022 | 65 | 2022 |
| Federated user representation learning D Bui, K Malik, J Goetz, H Liu, S Moon, A Kumar, KG Shin arXiv preprint arXiv:1909.12535, 2019 | 44 | 2019 |
| Papaya: Practical, private, and scalable federated learning D Huba, J Nguyen, K Malik, R Zhu, M Rabbat, A Yousefpour, CJ Wu, ... Proceedings of Machine Learning and Systems 4, 814-832, 2022 | 28 | 2022 |
| Exploiting postdominance for speculative parallelization M Agarwal, K Malik, KM Woley, SS Stone, MI Frank 2007 IEEE 13th International Symposium on High Performance Computer …, 2007 | 26 | 2007 |
| Federated learning with partial model personalization K Pillutla, K Malik, AR Mohamed, M Rabbat, M Sanjabi, L Xiao International Conference on Machine Learning, 17716-17758, 2022 | 20 | 2022 |
| Personalized Federated Learning for Assistant Systems K Malik, S Moon, LIU Honglei, A Kumar, H Zhan, A Aly US Patent App. 16/815,990, 2021 | 19 | 2021 |
| Paco: Probability-based path confidence prediction K Malik, M Agarwal, V Dhar, MI Frank 2008 IEEE 14th International Symposium on High Performance Computer …, 2008 | 18 | 2008 |
| Fetch-criticality reduction through control independence M Agarwal, N Navale, K Malik, MI Frank ACM SIGARCH Computer Architecture News 36 (3), 13-24, 2008 | 11 | 2008 |
| Fedsynth: Gradient compression via synthetic data in federated learning S Hu, J Goetz, K Malik, H Zhan, Z Liu, Y Liu arXiv preprint arXiv:2204.01273, 2022 | 9 | 2022 |
| Where to begin? exploring the impact of pre-training and initialization in federated learning J Nguyen, K Malik, M Sanjabi, M Rabbat arXiv preprint arXiv:2206.15387, 2022 | 7 | 2022 |
| Branch-mispredict level parallelism (BLP) for control independence K Malik, M Agarwal, SS Stone, KM Woley, MI Frank 2008 IEEE 14th International Symposium on High Performance Computer …, 2008 | 7 | 2008 |
| Active federated learning. arXiv 2019 J Goetz, K Malik, D Bui, S Moon, H Liu, A Kumar arXiv preprint arXiv:1909.12641, 0 | 5 | |
| Confidence based out-of-order renaming for speculatively multithreaded processors K Malik, KM Woley, SS Stone, M Agarwal, V Dhar, MI Frank Coordinated Science Laboratory Report no. UILU-ENG-06-2208, CRHC-06-04, 2006 | 4 | 2006 |
| Confidence based out-of-order register renaming for dynamically multithreaded processors K Malik University of Illinois at Urbana-Champaign, 2006 | 3 | 2006 |
| Voice-based Auto-Completions and Auto-Responses for Assistant Systems F Botros, N Wang, F Wang, MPD EDIZ, O Muzaffar, K Malik, ... US Patent App. 17/120,013, 2022 | 2 | 2022 |
| Adaptive memory synchronization (AMS): Balancing the risks and benefits of inter-thread load speculation K Malik, M Agarwal, MI Frank Reconfigurable and Adaptive Architecture Workshop, 2008 | 2 | 2008 |
| Synchronizing store sets (SSS): Balancing the benefits and risks of inter-thread load speculation SS Stone, KM Woley, K Malik, M Agarwal, V Dhar, MI Frank Coordinated Science Laboratory Report no. UILU-ENG-06-2221, CRHC-06-14, 2006 | 2 | 2006 |
| Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning J Nguyen, J Wang, K Malik, M Sanjabi, M Rabbat arXiv preprint arXiv:2210.08090, 2022 | 1 | 2022 |
| Critical branches and lucky loads in Control-Independence architectures K Malik University of Illinois at Urbana-Champaign, 2009 | 1 | 2009 |
Matthew FrankVerified email at illinois.edu
