Rama Kumar Pasumarthi

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 16

Top Topics

Boosted Decision Trees

Interaction Networks

Learning To Rank

Top Venues

Publications

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)
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 (2023)
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)
Le Yan, Zhen Qin, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky
Diversification-Aware Learning to Rank using Distributed Representation. WWW (2021)
Rolf Jagerman, Weize Kong, Rama Kumar Pasumarthi, Zhen Qin, Michael Bendersky, Marc Najork
Improving Cloud Storage Search with User Activity. WSDM (2021)
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)
Rama Kumar Pasumarthi, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork
Permutation Equivariant Document Interaction Network for Neural Learning to Rank. ICTIR (2020)
Brandon Tran, Maryam Karimzadehgan, Rama Kumar Pasumarthi, Michael Bendersky, Donald Metzler
Domain Adaptation for Enterprise Email Search. SIGIR (2019)
Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork
Self-Attentive Document Interaction Networks for Permutation Equivariant Ranking. CoRR (2019)
Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang
Neural Learning to Rank using TensorFlow Ranking: A Hands-on Tutorial. ICTIR (2019)
Brandon Tran, Maryam Karimzadehgan, Rama Kumar Pasumarthi, Michael Bendersky, Donald Metzler
Domain Adaptation for Enterprise Email Search. CoRR (2019)
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)
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)
Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, Ruslan Salakhutdinov
Gated-Attention Architectures for Task-Oriented Language Grounding. AAAI (2018)
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 (2018)
Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, Ruslan Salakhutdinov
Gated-Attention Architectures for Task-Oriented Language Grounding. CoRR (2017)
Varun R. Embar, Rama Kumar Pasumarthi, Indrajit Bhattacharya
A bayesian framework for estimating properties of network diffusions. KDD (2014)
Rama Kumar Pasumarthi, Srinivas Karthik, Ayush Choure, Vinayaka Pandit
Online network inference under dynamic cascade updates: A node-centric approach. COMSNETS (2014)
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) (2012)