| Deja vu: Contextual sparsity for efficient llms at inference time Z Liu, J Wang, T Dao, T Zhou, B Yuan, Z Song, A Shrivastava, C Zhang, ... International Conference on Machine Learning, 22137-22176, 2023 | 167 | 2023 |
| Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time Z Liu, A Desai, F Liao, W Wang, V Xie, Z Xu, A Kyrillidis, A Shrivastava Advances in Neural Information Processing Systems 36, 2024 | 84 | 2024 |
| Mongoose: A learnable lsh framework for efficient neural network training B Chen, Z Liu, B Peng, Z Xu, JL Li, T Dao, Z Song, A Shrivastava, C Re International Conference on Learning Representations, 2020 | 76 | 2020 |
| Guigle: A gui search engine for android apps C Bernal-Cárdenas, K Moran, M Tufano, Z Liu, L Nan, Z Shi, ... 2019 IEEE/ACM 41st International Conference on Software Engineering …, 2019 | 35* | 2019 |
| Efficient and less centralized federated learning L Chou, Z Liu, Z Wang, A Shrivastava Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 28 | 2021 |
| Learning Multimodal Data Augmentation in Feature Space Z Liu, Z Tang, X Shi, A Zhang, M Li, A Shrivastava, AG Wilson ICLR, 2022 | 14 | 2022 |
| Halos: Hashing large output space for cheap inference Z Liu, Z Xu, A Ji, J Zhang, J Li, B Chen, A Shrivastava Proceedings of Machine Learning and Systems 4, 110-125, 2022 | 9* | 2022 |
| One-pass distribution sketch for measuring data heterogeneity in federated learning Z Liu, Z Xu, B Coleman, A Shrivastava Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| Retaining Knowledge for Learning with Dynamic Definition Z Liu, B Coleman, T Zhang, A Shrivastava Advances in Neural Information Processing Systems, 2022 | 2 | 2022 |
| Wisdom of Committee: Distilling from Foundation Model to SpecializedApplication Model Z Liu, Q Liu, Y Li, L Liu, A Shrivastava, S Bi, L Hong, EH Chi, Z Zhao arXiv preprint arXiv:2402.14035, 2024 | 1 | 2024 |
| Heterogeneous federated collaborative filtering using FAIR: Federated Averaging in Random Subspaces A Desai, B Meisburger, Z Liu, A Shrivastava arXiv preprint arXiv:2311.01722, 2023 | 1 | 2023 |
| Efficient Inference via Universal LSH Kernel Z Liu, B Coleman, A Shrivastava arXiv preprint arXiv:2106.11426, 2021 | | 2021 |
| Neighbor Oblivious Learning (NObLe) for Device Localization and Tracking Z Liu, L Chou, A Shrivastava 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2021 | | 2021 |
Anshumali ShrivastavaRice University, ThirdAI Corp.Vahvistettu sähköpostiosoite verkkotunnuksessa rice.edu
