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ORCIDRama Kumar Pasumarthi
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2020 – today
- 2023
[c13]Zhen Qin, Rolf Jagerman, Rama Kumar Pasumarthi, Honglei Zhuang, He Zhang, Aijun Bai, Kai Hui, Le Yan, Xuanhui Wang:
RD-Suite: A Benchmark for Ranking Distillation. NeurIPS 2023- [i5]Zhen Qin, Rolf Jagerman, Rama Kumar Pasumarthi, Honglei Zhuang, He Zhang, Aijun Bai, Kai Hui, Le Yan, Xuanhui Wang:
RD-Suite: A Benchmark for Ranking Distillation. CoRR abs/2306.04455 (2023) - 2021
- [c12]Sashank J. Reddi, Rama Kumar Pasumarthi, Aditya Krishna Menon, Ankit Singh Rawat, Felix X. Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar:
RankDistil: Knowledge Distillation for Ranking. AISTATS 2021: 2368-2376 - [c11]Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork:
Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees? ICLR 2021 - [c10]Rolf Jagerman
, Weize Kong, Rama Kumar Pasumarthi, Zhen Qin, Michael Bendersky, Marc Najork:
Improving Cloud Storage Search with User Activity. WSDM 2021: 508-516 - [c9]Le Yan, Zhen Qin, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky:
Diversification-Aware Learning to Rank using Distributed Representation. WWW 2021: 127-136 - 2020
- [c8]Rama Kumar Pasumarthi, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork:
Permutation Equivariant Document Interaction Network for Neural Learning to Rank. ICTIR 2020: 145-148
2010 – 2019
- 2019
- [c7]Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang:
Neural Learning to Rank using TensorFlow Ranking: A Hands-on Tutorial. ICTIR 2019: 253-254 - [c6]Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf:
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. KDD 2019: 2970-2978 - [c5]Brandon Tran, Maryam Karimzadehgan, Rama Kumar Pasumarthi, Michael Bendersky, Donald Metzler:
Domain Adaptation for Enterprise Email Search. SIGIR 2019: 25-34 - [c4]Claudio Lucchese, Franco Maria Nardini, Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang, Harrie Oosterhuis, Rolf Jagerman, Maarten de Rijke:
Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning. SIGIR 2019: 1419-1420 - [i4]Brandon Tran, Maryam Karimzadehgan, Rama Kumar Pasumarthi, Michael Bendersky, Donald Metzler:
Domain Adaptation for Enterprise Email Search. CoRR abs/1906.07897 (2019) - [i3]Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork:
Self-Attentive Document Interaction Networks for Permutation Equivariant Ranking. CoRR abs/1910.09676 (2019) - 2018
- [c3]Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, Ruslan Salakhutdinov:
Gated-Attention Architectures for Task-Oriented Language Grounding. AAAI 2018: 2819-2826 - [i2]Rama Kumar Pasumarthi, Xuanhui Wang, Cheng Li, Sebastian Bruch, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf:
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. CoRR abs/1812.00073 (2018) - 2017
- [i1]Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, Ruslan Salakhutdinov:
Gated-Attention Architectures for Task-Oriented Language Grounding. CoRR abs/1706.07230 (2017) - 2014
- [c2]Rama Kumar Pasumarthi, Srinivas Karthik, Ayush Choure, Vinayaka Pandit:
Online network inference under dynamic cascade updates: A node-centric approach. COMSNETS 2014: 1-6 - [c1]Varun R. Embar, Rama Kumar Pasumarthi, Indrajit Bhattacharya:
A bayesian framework for estimating properties of network diffusions. KDD 2014: 1216-1225 - 2012
- [j1]Rama Kumar Pasumarthi, V. R. Devanathan, V. Visvanathan, Seetal Potluri, V. Kamakoti:
Thermal-Safe Dynamic Test Scheduling Method Using On-Chip Temperature Sensors for 3D MPSoCs. J. Low Power Electron. 8(5): 684-695 (2012)
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