| Moment-based quantile sketches for efficient high cardinality aggregation queries E Gan, J Ding, KS Tai, V Sharan, P Bailis arXiv preprint arXiv:1803.01969, 2018 | 61 | 2018 |
| Sketching linear classifiers over data streams KS Tai, V Sharan, P Bailis, G Valiant Proceedings of the 2018 international conference on management of data, 757-772, 2018 | 47 | 2018 |
| Orthogonalized ALS: A theoretically principled tensor decomposition algorithm for practical use V Sharan, G Valiant International Conference on Machine Learning, 3095-3104, 2017 | 46 | 2017 |
| Memory-sample tradeoffs for linear regression with small error V Sharan, A Sidford, G Valiant Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 36 | 2019 |
| Prediction with a short memory V Sharan, S Kakade, P Liang, G Valiant Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018 | 36* | 2018 |
| Omnipredictors P Gopalan, AT Kalai, O Reingold, V Sharan, U Wieder arXiv preprint arXiv:2109.05389, 2021 | 33 | 2021 |
| A spectral view of adversarially robust features S Garg, V Sharan, B Zhang, G Valiant Advances in Neural Information Processing Systems 31, 2018 | 28 | 2018 |
| Pidforest: anomaly detection via partial identification P Gopalan, V Sharan, U Wieder Advances in Neural Information Processing Systems 32, 2019 | 22 | 2019 |
| Learning overcomplete hmms V Sharan, SM Kakade, PS Liang, G Valiant Advances in Neural Information Processing Systems 30, 2017 | 20 | 2017 |
| Energy efficient optimal node-source localization using mobile beacon in ad-hoc sensor networks S Kumar, V Sharan, RM Hegde 2013 IEEE global communications conference (GLOBECOM), 487-492, 2013 | 19 | 2013 |
| Compressed factorization: Fast and accurate low-rank factorization of compressively-sensed data V Sharan, KS Tai, P Bailis, G Valiant International Conference on Machine Learning, 5690-5700, 2019 | 17 | 2019 |
| Efficient convex optimization requires superlinear memory A Marsden, V Sharan, A Sidford, G Valiant Conference on Learning Theory, 2390-2430, 2022 | 15 | 2022 |
| Efficient anomaly detection via matrix sketching V Sharan, P Gopalan, U Wieder Advances in neural information processing systems 31, 2018 | 14* | 2018 |
| Sample amplification: Increasing dataset size even when learning is impossible B Axelrod, S Garg, V Sharan, G Valiant International Conference on Machine Learning, 442-451, 2020 | 10 | 2020 |
| Multicalibrated partitions for importance weights P Gopalan, O Reingold, V Sharan, U Wieder International Conference on Algorithmic Learning Theory, 408-435, 2022 | 9 | 2022 |
| One network fits all? modular versus monolithic task formulations in neural networks A Agarwala, A Das, B Juba, R Panigrahy, V Sharan, X Wang, Q Zhang arXiv preprint arXiv:2103.15261, 2021 | 9 | 2021 |
| Recovery guarantees for quadratic tensors with sparse observations H Zhang, V Sharan, M Charikar, Y Liang The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 9* | 2019 |
| Spectrum sensing for cognitive radio V Sharan, P Wankhede International Journal of Communication Networks and Information Security …, 2013 | 4 | 2013 |
| NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks S Zeighami, C Shahabi, V Sharan Proceedings of the ACM on Management of Data 1 (1), 1-26, 2023 | 2 | 2023 |
| Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales J Kelner, A Marsden, V Sharan, A Sidford, G Valiant, H Yuan Conference on Learning Theory, 2431-2540, 2022 | 2 | 2022 |
Gregory ValiantAssistant Professor of Computer Science, Stanford UniversityVerified email at stanford.edu
