| Learning structural node embeddings via diffusion wavelets C Donnat, M Zitnik, D Hallac, J Leskovec Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018 | 438 | 2018 |
| Toeplitz inverse covariance-based clustering of multivariate time series data D Hallac, S Vare, S Boyd, J Leskovec Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 338 | 2017 |
| Network lasso: Clustering and optimization in large graphs D Hallac, J Leskovec, S Boyd Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 326 | 2015 |
| Network inference via the time-varying graphical lasso D Hallac, Y Park, S Boyd, J Leskovec Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 236 | 2017 |
| Data-driven model predictive control of autonomous mobility-on-demand systems R Iglesias, F Rossi, K Wang, D Hallac, J Leskovec, M Pavone 2018 IEEE international conference on robotics and automation (ICRA), 6019-6025, 2018 | 162 | 2018 |
| Driver identification using automobile sensor data from a single turn D Hallac, A Sharang, R Stahlmann, A Lamprecht, M Huber, M Roehder, ... 2016 IEEE 19th International Conference on Intelligent Transportation …, 2016 | 161 | 2016 |
| Greedy Gaussian segmentation of multivariate time series D Hallac, P Nystrup, S Boyd Advances in Data Analysis and Classification 13 (3), 727-751, 2019 | 90 | 2019 |
| Drive2vec: Multiscale state-space embedding of vehicular sensor data D Hallac, S Bhooshan, M Chen, K Abida, J Leskovec 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 40 | 2018 |
| SnapVX: A network-based convex optimization solver D Hallac, C Wong, S Diamond, A Sharang, S Boyd, J Leskovec Journal of Machine Learning Research 18 (4), 1-5, 2017 | 30 | 2017 |
| Learning the network structure of heterogeneous data via pairwise exponential Markov random fields Y Park, D Hallac, S Boyd, J Leskovec Artificial Intelligence and Statistics, 1302-1310, 2017 | 23 | 2017 |
| Driver2vec: Driver identification from automotive data J Yang, R Zhao, M Zhu, D Hallac, J Sodnik, J Leskovec arXiv preprint arXiv:2102.05234, 2021 | 16 | 2021 |
| Distributed majorization-minimization for Laplacian regularized problems J Tuck, D Hallac, S Boyd IEEE/CAA Journal of Automatica Sinica 6 (1), 45-52, 2019 | 12 | 2019 |
| MASA: Motif-aware state assignment in noisy time series data S Jain, D Hallac, R Sosic, J Leskovec arXiv preprint arXiv:1809.01819, 2018 | 10* | 2018 |
| High Dimensional Models TVG Lasso, D Hallac, Y Park, S Boyd, J Leskovec, A Boomer, ... | | 2021 |
| Inferring Structure from Multivariate Time Series Sensor Data DP Hallac Stanford University, 2018 | | 2018 |
| Network Lasso D Hallac, J Leskovec, S Boyd Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | | 2015 |
| ECE 602 Project: Implementation of" Network Inference via the Time-Varying Graphical Lasso D Hallac, Y Park, S Boyd, J Leskovec, A Main | | |
| Scalable Machine Learning on Spark for multiclass problems G Kamath, S Dhar, N Ramakrishnan, D Hallac, J Leskovec, M Shah | | |
Jure LeskovecProfessor of Computer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
