| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023 | 3600 | 2023 |
| Gated-Attention Architectures for Task-Oriented Language Grounding RS Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar ... 32nd AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, USA, 2018 | 285* | 2018 |
| TF-Ranking: Scalable tensorflow library for learning-to-rank RK Pasumarthi, S Bruch, X Wang, C Li, M Bendersky, M Najork, J Pfeifer, ... Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 169 | 2019 |
| Are neural rankers still outperformed by gradient boosted decision trees? Z Qin, L Yan, H Zhuang, Y Tay, RK Pasumarthi, X Wang, M Bendersky, ... International conference on learning representations, 2021 | 126 | 2021 |
| Diversification-aware learning to rank using distributed representation L Yan, Z Qin, RK Pasumarthi, X Wang, M Bendersky Proceedings of the Web Conference 2021, 127-136, 2021 | 44 | 2021 |
| Permutation equivariant document interaction network for neural learning to rank RK Pasumarthi, H Zhuang, X Wang, M Bendersky, M Najork Proceedings of the 2020 ACM SIGIR on international conference on theory of …, 2020 | 39* | 2020 |
| Rankdistil: Knowledge distillation for ranking S Reddi, RK Pasumarthi, A Menon, AS Rawat, F Yu, S Kim, A Veit, ... International Conference on Artificial Intelligence and Statistics, 2368-2376, 2021 | 36 | 2021 |
| Domain adaptation for enterprise email search B Tran, M Karimzadehgan, RK Pasumarthi, M Bendersky, D Metzler Proceedings of the 42nd international ACM SIGIR Conference on Research and …, 2019 | 26 | 2019 |
| Near Optimal Strategies for Targeted Marketing in Social Networks R Pasumarthi, R Narayanam, B Ravindran Proceedings of the 2015 International Conference on Autonomous Agents and …, 2015 | 20 | 2015 |
| Neutralizing propagation of malicious information P Agrawal, P Banerjee, R Kokku, SRK Pasumarthi US Patent 9,342,692, 2016 | 18 | 2016 |
| Learning to rank in theory and practice: from gradient boosting to neural networks and unbiased learning C Lucchese, FM Nardini, RK Pasumarthi, S Bruch, M Bendersky, X Wang, ... Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 13 | 2019 |
| A Bayesian Framework for Estimating Properties of Network Diffusions VR Embar, RK Pasumarthi, I Bhattacharya Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 13 | 2014 |
| Building cmu magnus from user feedback S Prabhumoye, F Botros, K Chandu, S Choudhary, E Keni, C Malaviya, ... Alexa Prize Proceedings, 2017 | 7 | 2017 |
| Rd-suite: A benchmark for ranking distillation Z Qin, R Jagerman, RK Pasumarthi, H Zhuang, H Zhang, A Bai, K Hui, ... Advances in Neural Information Processing Systems 36, 2023 | 6 | 2023 |
| Neural learning to rank using tensorflow ranking: A hands-on tutorial RK Pasumarthi, S Bruch, M Bendersky, X Wang Proceedings of the 2019 ACM SIGIR International Conference on Theory of …, 2019 | 5 | 2019 |
| Improving cloud storage search with user activity R Jagerman, W Kong, RK Pasumarthi, Z Qin, M Bendersky, M Najork Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 2 | 2021 |
| Thermal-Safe Dynamic Test Scheduling Method Using On-Chip Temperature Sensors for 3D MPSoCs RK Pasumarthi, VR Devanathan, V Visvanathan, S Potluri, V Kamakoti Journal of Low Power Electronics 8 (5), 684-695, 2012 | 2 | 2012 |
| Systems and methods for using document activity logs to train machine-learned models for determining document relevance W Kong, M Bendersky, M Najork, RK Pasumarthi, Z Qin, R Jagerman US Patent App. 18/010,727, 2023 | 1 | 2023 |
| Online Network Inference under Dynamic Cascade Updates: A Node-Centric Approach RK Pasumarthi, S Karthik, A Choure, V Pandit 2014 Sixth International Conference on Communication Systems and Networks …, 2014 | 1 | 2014 |
| Sparse Network Inference using the k-Support Norm A Gupta, H Wang, RK Pasumarthi 12th International Workshop on Mining and Learning with Graphs, 2016 | | 2016 |
Michael BenderskyGoogle DeepMindEmail verificata su google.com
