| Distributed graphlab: A framework for machine learning in the cloud Y Low, J Gonzalez, A Kyrola, D Bickson, C Guestrin, JM Hellerstein arXiv preprint arXiv:1204.6078, 2012 | 2105 | 2012 |
| Yucheng Low, Haijie Gu, Danny Bickson, Carlos Guestrin, PowerGraph: distributed graph-parallel computation on natural graphs JE Gonzalez Proceedings of the 10th USENIX conference on Operating Systems Design and …, 2012 | 1876* | 2012 |
| Powergraph: Distributed graph-parallel computation on natural graphs JE Gonzalez, Y Low, H Gu, D Bickson, C Guestrin Presented as part of the 10th {USENIX} Symposium on Operating Systems Design …, 2012 | 1876 | 2012 |
| Apache spark: a unified engine for big data processing M Zaharia, RS Xin, P Wendell, T Das, M Armbrust, A Dave, X Meng, ... Communications of the ACM 59 (11), 56-65, 2016 | 1691 | 2016 |
| Graphx: Graph processing in a distributed dataflow framework JE Gonzalez, RS Xin, A Dave, D Crankshaw, MJ Franklin, I Stoica 11th {USENIX} Symposium on Operating Systems Design and Implementation …, 2014 | 1103 | 2014 |
| Graphlab: A new framework for parallel machine learning Y Low, JE Gonzalez, A Kyrola, D Bickson, CE Guestrin, J Hellerstein arXiv preprint arXiv:1408.2041, 2014 | 905 | 2014 |
| Graphx: A resilient distributed graph system on spark RS Xin, JE Gonzalez, MJ Franklin, I Stoica First international workshop on graph data management experiences and …, 2013 | 772 | 2013 |
| Graphlab: A new parallel framework for machine learning Y Low, J Gonzalez, A Kyrola, D Bickson, C Guestrin, JM Hellerstein Conference on uncertainty in artificial intelligence (UAI) 20, 2010 | 436 | 2010 |
| Scalable inference in latent variable models A Ahmed, M Aly, J Gonzalez, S Narayanamurthy, AJ Smola Proceedings of the fifth ACM international conference on Web search and data …, 2012 | 299 | 2012 |
| Clipper: A low-latency online prediction serving system D Crankshaw, X Wang, G Zhou, MJ Franklin, JE Gonzalez, I Stoica 14th {USENIX} Symposium on Networked Systems Design and Implementation …, 2017 | 247 | 2017 |
| Opaque: An oblivious and encrypted distributed analytics platform W Zheng, A Dave, JG Beekman, RA Popa, JE Gonzalez, I Stoica 14th {USENIX} Symposium on Networked Systems Design and Implementation …, 2017 | 233 | 2017 |
| Skipnet: Learning dynamic routing in convolutional networks X Wang, F Yu, ZY Dou, T Darrell, JE Gonzalez Proceedings of the European Conference on Computer Vision (ECCV), 409-424, 2018 | 217 | 2018 |
| MLI: An API for distributed machine learning ER Sparks, A Talwalkar, V Smith, J Kottalam, X Pan, J Gonzalez, ... 2013 IEEE 13th International Conference on Data Mining, 1187-1192, 2013 | 203 | 2013 |
| Cloud programming simplified: A berkeley view on serverless computing E Jonas, J Schleier-Smith, V Sreekanti, CC Tsai, A Khandelwal, Q Pu, ... arXiv preprint arXiv:1902.03383, 2019 | 197 | 2019 |
| Residual splash for optimally parallelizing belief propagation J Gonzalez, Y Low, C Guestrin Artificial Intelligence and Statistics, 177-184, 2009 | 181 | 2009 |
| Shift: A zero flop, zero parameter alternative to spatial convolutions B Wu, A Wan, X Yue, P Jin, S Zhao, N Golmant, A Gholaminejad, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 178 | 2018 |
| RLlib: Abstractions for distributed reinforcement learning E Liang, R Liaw, R Nishihara, P Moritz, R Fox, K Goldberg, J Gonzalez, ... International Conference on Machine Learning, 3053-3062, 2018 | 171 | 2018 |
| Serverless computing: One step forward, two steps back JM Hellerstein, J Faleiro, JE Gonzalez, J Schleier-Smith, V Sreekanti, ... arXiv preprint arXiv:1812.03651, 2018 | 163 | 2018 |
| Parallel gibbs sampling: From colored fields to thin junction trees J Gonzalez, Y Low, A Gretton, C Guestrin Proceedings of the Fourteenth International Conference on Artificial …, 2011 | 159 | 2011 |
| A berkeley view of systems challenges for ai I Stoica, D Song, RA Popa, D Patterson, MW Mahoney, R Katz, ... arXiv preprint arXiv:1712.05855, 2017 | 141 | 2017 |
