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 | 68 | 2018 |
Orthogonalized ALS: A theoretically principled tensor decomposition algorithm for practical use V Sharan, G Valiant International Conference on Machine Learning, 3095-3104, 2017 | 51 | 2017 |
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 | 50 | 2018 |
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 | 44 | 2019 |
Omnipredictors P Gopalan, AT Kalai, O Reingold, V Sharan, U Wieder arXiv preprint arXiv:2109.05389, 2021 | 43 | 2021 |
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 | 40* | 2018 |
Pidforest: anomaly detection via partial identification P Gopalan, V Sharan, U Wieder Advances in Neural Information Processing Systems 32, 2019 | 33 | 2019 |
A spectral view of adversarially robust features S Garg, V Sharan, B Zhang, G Valiant Advances in Neural Information Processing Systems 31, 2018 | 32 | 2018 |
Learning overcomplete hmms V Sharan, SM Kakade, PS Liang, G Valiant Advances in Neural Information Processing Systems 30, 2017 | 21 | 2017 |
Efficient convex optimization requires superlinear memory A Marsden, V Sharan, A Sidford, G Valiant Conference on Learning Theory, 2390-2430, 2022 | 20 | 2022 |
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 anomaly detection via matrix sketching V Sharan, P Gopalan, U Wieder Advances in neural information processing systems 31, 2018 | 17* | 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 | 16 | 2020 |
Transformers learn higher-order optimization methods for in-context learning: A study with linear models D Fu, TQ Chen, R Jia, V Sharan arXiv preprint arXiv:2310.17086, 2023 | 15 | 2023 |
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 | 15 | 2021 |
Multicalibrated partitions for importance weights P Gopalan, O Reingold, V Sharan, U Wieder International Conference on Algorithmic Learning Theory, 408-435, 2022 | 11 | 2022 |
Fairness in matching under uncertainty S Devic, D Kempe, V Sharan, A Korolova International Conference on Machine Learning, 7775-7794, 2023 | 8 | 2023 |
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 | 7 | 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 | 5 | 2022 |