Using deep learning to enhance cancer diagnosis and classification R Fakoor, F Ladhak, A Nazi, M Huber The 30th International Conference on Machine Learning (ICML 2013), WHEALTH …, 2013 | 637 | 2013 |
A graph placement methodology for fast chip design A Mirhoseini, A Goldie, M Yazgan, JW Jiang, E Songhori, S Wang, YJ Lee, ... Nature 594 (7862), 207-212, 2021 | 578* | 2021 |
Chip placement with deep reinforcement learning A Mirhoseini, A Goldie, M Yazgan, J Jiang, E Songhori, S Wang, YJ Lee, ... arXiv preprint arXiv:2004.10746, 2020 | 236 | 2020 |
Selectivity estimation for range predicates using lightweight models A Dutt, C Wang, A Nazi, S Kandula, V Narasayya, S Chaudhuri Proceedings of the VLDB Endowment 12 (9), 1044-1057, 2019 | 191* | 2019 |
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024 | 154 | 2024 |
Teaching algorithmic reasoning via in-context learning H Zhou, A Nova, H Larochelle, A Courville, B Neyshabur, H Sedghi arXiv preprint arXiv:2211.09066, 2022 | 78* | 2022 |
Gap: Generalizable approximate graph partitioning framework A Nazi, W Hang, A Goldie, S Ravi, A Mirhoseini arXiv preprint arXiv:1903.00614, 2019 | 69 | 2019 |
Scalable deep generative modeling for sparse graphs H Dai, A Nazi, Y Li, B Dai, D Schuurmans International conference on machine learning, 2302-2312, 2020 | 66 | 2020 |
Efficient Computation of Regret-ratio Minimizing Set: A Compact Maxima Representative A Asudeh, A Nazi, N Zhang, G Das Proceedings of the 2017 International Conference on Management of Data (SIGMOD), 2017 | 54 | 2017 |
Walk, Not Wait: Faster Sampling Over Online Social Networks A Nazi, Z Zhou, S Thirumuruganathan, N Zhang, G Das http://arxiv.org/abs/1410.7833, 2014 | 39 | 2014 |
An integrated cloud-based framework for mobile phone sensing R Fakoor, M Raj, A Nazi, M Di Francesco, SK Das Proceedings of the first edition of the MCC workshop on Mobile cloud …, 2012 | 35 | 2012 |
Beyond human data: Scaling self-training for problem-solving with language models A Singh, JD Co-Reyes, R Agarwal, A Anand, P Patil, PJ Liu, J Harrison, ... arXiv preprint arXiv:2312.06585, 2023 | 34 | 2023 |
Deployment of robust wireless sensor networks using gene regulatory networks: An isomorphism-based approach A Nazi, M Raj, M Di Francesco, P Ghosh, SK Das Pervasive and Mobile Computing 13, 246-257, 2014 | 27 | 2014 |
RRR: Rank-regret representative A Asudeh, A Nazi, N Zhang, G Das, HV Jagadish Proceedings of the 2019 International Conference on Management of Data, 263-280, 2019 | 24* | 2019 |
Efficient communications in wireless sensor networks based on biological robustness A Nazi, M Raj, M Di Francesco, P Ghosh, SK Das 2016 International Conference on Distributed Computing in Sensor Systems …, 2016 | 22 | 2016 |
Robust deployment of wireless sensor networks using gene regulatory networks A Nazi, M Raj, M Di Francesco, P Ghosh, SK Das Distributed Computing and Networking: 14th International Conference, ICDCN …, 2013 | 22 | 2013 |
Efficient estimation of inclusion coefficient using hyperloglog sketches A Nazi, B Ding, V Narasayya, S Chaudhuri Proceedings of the VLDB Endowment 11 (10), 1097-1109, 2018 | 20 | 2018 |
Maximizing fair content spread via edge suggestion in social networks IP Swift, S Ebrahimi, A Nova, A Asudeh arXiv preprint arXiv:2207.07704, 2022 | 13 | 2022 |
The TagAdvisor: Luring the lurkers to review web items A Nazi, M Das, G Das Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015 | 12 | 2015 |
Many-shot in-context learning R Agarwal, A Singh, LM Zhang, B Bohnet, S Chan, A Anand, Z Abbas, ... arXiv preprint arXiv:2404.11018, 2024 | 11 | 2024 |