| Cellular network traffic scheduling with deep reinforcement learning S Chinchali, P Hu, T Chu, M Sharma, M Bansal, R Misra, M Pavone, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 96 | 2018 |
| Numfabric: Fast and flexible bandwidth allocation in datacenters K Nagaraj, D Bharadia, H Mao, S Chinchali, M Alizadeh, S Katti Proceedings of the 2016 ACM SIGCOMM Conference, 188-201, 2016 | 75 | 2016 |
| Scheduling packets over multiple interfaces while respecting user preferences KK Yap, TY Huang, Y Yiakoumis, S Chinchali, N McKeown, S Katti Proceedings of the ninth ACM conference on Emerging networking experiments …, 2013 | 41 | 2013 |
| Network offloading policies for cloud robotics: a learning-based approach S Chinchali, A Sharma, J Harrison, A Elhafsi, D Kang, E Pergament, ... arXiv preprint arXiv:1902.05703, 2019 | 31 | 2019 |
| Towards formal synthesis of reactive controllers for dexterous robotic manipulation S Chinchali, SC Livingston, U Topcu, JW Burdick, RM Murray 2012 IEEE International Conference on Robotics and Automation, 5183-5189, 2012 | 30 | 2012 |
| Neural networks meet physical networks: Distributed inference between edge devices and the cloud SP Chinchali, E Cidon, E Pergament, T Chu, S Katti Proceedings of the 17th ACM Workshop on Hot Topics in Networks, 50-56, 2018 | 18 | 2018 |
| Axel rover paddle wheel design, efficiency, and sinkage on deformable terrain P Abad-Manterola, JW Burdick, IAD Nesnas, S Chinchali, C Fuller, X Zhou 2010 IEEE International Conference on Robotics and Automation, 2821-2827, 2010 | 14 | 2010 |
| Erosion of conserved binding sites in personal genomes points to medical histories H Guturu, S Chinchali, SL Clarke, G Bejerano PLoS computational biology 12 (2), e1004711, 2016 | 10 | 2016 |
| Multi-agent reinforcement learning for networked system control T Chu, S Chinchali, S Katti arXiv preprint arXiv:2004.01339, 2020 | 8 | 2020 |
| Multi-objective optimal control for proactive decision making with temporal logic models SP Chinchali, SC Livingston, M Chen, M Pavone The International Journal of Robotics Research 38 (12-13), 1490-1512, 2019 | 7 | 2019 |
| Simultaneous model identification and task satisfaction in the presence of temporal logic constraints SP Chinchali, SC Livingston, M Pavone, JW Burdick 2016 IEEE International Conference on Robotics and Automation (ICRA), 3682-3689, 2016 | 4 | 2016 |
| Deep Learning for Wireless Interference Segmentation and Prediction S Chinchali, S Tandon | 3 | 2012 |
| Sampling Training Data for Continual Learning Between Robots and the Cloud S Chinchali, E Pergament, M Nakanoya, E Cidon, E Zhang, D Bharadia, ... arXiv preprint arXiv:2012.06739, 2020 | | 2020 |
| Task-relevant Representation Learning for Networked Robotic Perception M Nakanoya, S Chinchali, A Anemogiannis, A Datta, S Katti, M Pavone arXiv preprint arXiv:2011.03216, 2020 | | 2020 |
| System and method for widescale adaptive bitrate selection T Chu, R Misra, S Chinchali, A Anemogiannis, R Tandra, K Nagaraj US Patent App. 16/582,089, 2020 | | 2020 |
| Collaborative Perception and Learning Between Robots and the Cloud SP Chinchali Stanford University, 2020 | | 2020 |
| HarvestNet: Mining Valuable Training Data from High-Volume Robot Sensory Streams S Chinchali, E Pergament, M Nakanoya, E Cidon, E Zhang, D Bharadia, ... | | |
| Cellular Network Traffic Scheduling using Deep Reinforcement Learning S Chinchali, M Pavone, S Katti | | |
