Xoring elephants: Novel erasure codes for big data M Sathiamoorthy, M Asteris, D Papailiopoulos, AG Dimakis, R Vadali, ... arXiv preprint arXiv:1301.3791, 2013 | 915 | 2013 |
Recommending what video to watch next: a multitask ranking system Z Zhao, L Hong, L Wei, J Chen, A Nath, S Andrews, A Kumthekar, ... Proceedings of the 13th ACM conference on recommender systems, 43-51, 2019 | 362 | 2019 |
Spatially-localized compressed sensing and routing in multi-hop sensor networks S Lee, S Pattem, M Sathiamoorthy, B Krishnamachari, A Ortega International conference on geosensor networks, 11-20, 2009 | 113 | 2009 |
Dselect-k: Differentiable selection in the mixture of experts with applications to multi-task learning H Hazimeh, Z Zhao, A Chowdhery, M Sathiamoorthy, Y Chen, ... Advances in Neural Information Processing Systems 34, 29335-29347, 2021 | 108 | 2021 |
Systems and methods for decreasing RAID rebuilding time M Sathiamoorthy, F Guo, AG Dimakis US Patent 9,594,652, 2017 | 104 | 2017 |
Backpressure with adaptive redundancy (BWAR) M Alresaini, M Sathiamoorthy, B Krishnamachari, MJ Neely 2012 Proceedings IEEE INFOCOM, 2300-2308, 2012 | 78 | 2012 |
Do llms understand user preferences? evaluating llms on user rating prediction WC Kang, J Ni, N Mehta, M Sathiamoorthy, L Hong, E Chi, DZ Cheng arXiv preprint arXiv:2305.06474, 2023 | 71 | 2023 |
Compressed sensing and routing in multi-hop networks S Lee, S Pattem, M Sathiamoorthy, B Krishnamachari, A Ortega University of Southern California CENG technical report, 2009 | 71 | 2009 |
Recommender systems with generative retrieval S Rajput, N Mehta, A Singh, R Hulikal Keshavan, T Vu, L Heldt, L Hong, ... Advances in Neural Information Processing Systems 36, 2024 | 62 | 2024 |
Distributed storage codes reduce latency in vehicular networks M Sathiamoorthy, AG Dimakis, B Krishnamachari, F Bai IEEE Transactions on Mobile Computing 13 (9), 2016-2027, 2013 | 54 | 2013 |
Optimizing content dissemination in vehicular networks with radio heterogeneity J Ahn, M Sathiamoorthy, B Krishnamachari, F Bai, L Zhang IEEE Transactions on Mobile Computing 13 (6), 1312-1325, 2013 | 27 | 2013 |
Lifting the curse of multidimensional data with learned existence indexes S Macke, A Beutel, T Kraska, M Sathiamoorthy, DZ Cheng, EH Chi Workshop on ML for Systems at NeurIPS 1, 6, 2018 | 22 | 2018 |
Helper node allocation strategies for content dissemination in intermittently connected mobile networks M Sathiamoorthy, KR Moghadam, B Krishnamachari, F Bai 2014 Eleventh Annual IEEE International Conference on Sensing, Communication …, 2014 | 10 | 2014 |
Do LLMs understand user preferences WC Kang, J Ni, N Mehta, M Sathiamoorthy, L Hong, E Chi, DZ Cheng Evaluating LLMs On User Rating Prediction. CoRR abs/2305.06474, 2023 | 8 | 2023 |
Compressed sensing and routing in sensor networks S Lee, S Pattem, M Sathiamoorthy, B Krishnamachari, A Ortega Univ. Southern California, Los Angeles, CA, USA, Tech. Rep, 2009 | 8 | 2009 |
Chi, and Derek Zhiyuan Cheng. Do llms understand user preferences? evaluating llms on user rating prediction WC Kang, J Ni, N Mehta, M Sathiamoorthy, L Hong arXiv preprint arXiv:2305.06474, 2023 | 7 | 2023 |
Improving training stability for multitask ranking models in recommender systems J Tang, Y Drori, D Chang, M Sathiamoorthy, J Gilmer, L Wei, X Yi, L Hong, ... Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 6 | 2023 |
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys) Y Deldjoo, Z He, J McAuley, A Korikov, S Sanner, A Ramisa, R Vidal, ... arXiv preprint arXiv:2404.00579, 2024 | 5 | 2024 |
Nonlinear initialization methods for low-rank neural networks K Vodrahalli, R Shivanna, M Sathiamoorthy, S Jain, EH Chi arXiv preprint arXiv:2202.00834, 2022 | 5 | 2022 |
Opportunities and challenges of machine learning accelerators in production R Ananthanarayanan, P Brandt, M Joshi, M Sathiamoorthy 2019 USENIX Conference on Operational Machine Learning (OpML 19), 1-3, 2019 | 3 | 2019 |