Követés
Maheswaran (Mahesh) Sathiamoorthy
Maheswaran (Mahesh) Sathiamoorthy
Bespoke Labs
E-mail megerősítve itt: bespokelabs.ai - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Xoring elephants: Novel erasure codes for big data
M Sathiamoorthy, M Asteris, D Papailiopoulos, AG Dimakis, R Vadali, ...
arXiv preprint arXiv:1301.3791, 2013
9292013
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
3952019
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
1292021
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
1132009
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, 10299-10315, 2023
1102023
Systems and methods for decreasing RAID rebuilding time
M Sathiamoorthy, F Guo, AG Dimakis
US Patent 9,594,652, 2017
1042017
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
972023
Backpressure with adaptive redundancy (BWAR)
M Alresaini, M Sathiamoorthy, B Krishnamachari, MJ Neely
2012 Proceedings IEEE INFOCOM, 2300-2308, 2012
792012
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
712009
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
552013
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, ...
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024
312024
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
272013
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
242018
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
122023
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
112023
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
102014
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
82023
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
82009
Aligning Large Language Models with Recommendation Knowledge
Y Cao, N Mehta, X Yi, R Keshavan, L Heldt, L Hong, EH Chi, ...
arXiv preprint arXiv:2404.00245, 2024
72024
Better generalization with semantic ids: A case study in ranking for recommendations
A Singh, T Vu, N Mehta, R Keshavan, M Sathiamoorthy, Y Zheng, L Hong, ...
Proceedings of the 18th ACM Conference on Recommender Systems, 1039-1044, 2024
52024
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