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ORCIDArun Rajkumar
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2020 – today
- 2024
[i12]Biswajit Rout, Ananya B. Sai, Arun Rajkumar:
Closing the Gap in the Trade-off between Fair Representations and Accuracy. CoRR abs/2404.09664 (2024)- 2023
- [c23]Utsav Dey, Arun Rajkumar, Lakshmi Narasimhan Theagarajan:
Linearly Constrained and Structured Reinforcement Learning Algorithm for Wireless Link Adaptation. WiOpt 2023: 562-569 - 2022
- [c22]Athul M. A, Arun Rajkumar:
Hyper-IMRANK: Ranking-based Influence Maximization for Hypergraphs. COMAD/CODS 2022: 100-104 - [c21]Arun Rajkumar, Vishnu Veerathu, Abdul Bakey Mir:
A Theory of Tournament Representations. ICLR 2022 - [c20]Arnhav Datar, Arun Rajkumar, John Augustine:
Byzantine Spectral Ranking. NeurIPS 2022 - [i11]Chandrashekar Lakshminarayanan, Amit Vikram Singh, Arun Rajkumar:
Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality. CoRR abs/2203.16455 (2022) - [i10]Arnhav Datar, Arun Rajkumar, John Augustine:
Byzantine Spectral Ranking. CoRR abs/2211.07902 (2022) - 2021
- [c19]Anant Shah, Arun Rajkumar:
Sequential Ski Rental Problem. AAMAS 2021: 1173-1181 - [c18]Dev Yashpal Sheth, Arun Rajkumar:
PARWiS: Winner determination from Active Pairwise Comparisons under a Shoestring Budget. ICDM 2021: 569-578 - [c17]Vishnu Veerathu, Arun Rajkumar:
On The Structure of Parametric Tournaments with Application to Ranking from Pairwise Comparisons. NeurIPS 2021: 12065-12076 - [i9]Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar, Raman Sankaran:
Censored Semi-Bandits for Resource Allocation. CoRR abs/2104.05781 (2021) - [i8]Anant Shah, Arun Rajkumar:
Sequential Ski Rental Problem. CoRR abs/2104.06050 (2021) - [i7]Arun Rajkumar, Vishnu Veerathu, Abdul Bakey Mir:
A Theory of Tournament Representations. CoRR abs/2110.05188 (2021) - 2020
- [c16]Dev Yashpal Sheth, Arun Rajkumar:
Active Ranking from Pairwise Comparisons with Dynamically Arriving Items and Voters. COMAD/CODS 2020: 229-233 - [i6]Sahil Manchanda
, Arun Rajkumar, Simarjot Kaur, Narayanan Unny:
SUPAID: A Rule mining based method for automatic rollout decision aid for supervisors in fleet management systems. CoRR abs/2001.03386 (2020)
2010 – 2019
- 2019
- [c15]Himanshu Sharad Bhatt, Shourya Roy, Arun Rajkumar, Sriranjani Ramakrishnan:
Learning Transferable Feature Representations Using Neural Networks. ACL (1) 2019: 4124-4134 - [c14]Prateek Yadav, Madhav Nimishakavi, Naganand Yadati, Shikhar Vashishth, Arun Rajkumar, Partha Pratim Talukdar:
Lovasz Convolutional Networks. AISTATS 2019: 1978-1987 - [c13]Jayati Bandyopadhyay, Nupur Labh, Simarjot Kaur, Arun Rajkumar, Sourav Bhattacharya, Saurabh Srivastava:
TrustCircle: a novel trust framework for creating a personalised recommender system that helps evaluate trustworthiness in sharing economy services. IndiaHCI 2019: 2:1-2:10 - [c12]Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar, Raman Sankaran:
Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback. NeurIPS 2019: 14499-14509 - [i5]Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar, Raman Sankaran:
Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback. CoRR abs/1909.01504 (2019) - 2018
- [c11]Raghu Krishnapuram, Arun Rajkumar, Adithya Acharya, Nikhil Dhara Venkata, Manjunath M. Goudar, Akshay P. Sarashetti:
Online domain adaptation by exploiting labeled features and pro-active learning. COMAD/CODS 2018: 137-145 - [i4]Prateek Yadav, Madhav Nimishakavi, Naganand Yadati, Arun Rajkumar, Partha Pratim Talukdar:
Lovasz Convolutional Networks. CoRR abs/1805.11365 (2018) - 2017
- [c10]U. N. Niranjan, Arun Rajkumar:
Inductive Pairwise Ranking: Going Beyond the n log(n) Barrier. AAAI 2017: 2436-2442 - [c9]Arun Rajkumar, Koyel Mukherjee, Theja Tulabandhula:
Learning to Partition using Score Based Compatibilities. AAMAS 2017: 574-582 - [c8]U. N. Niranjan, Arun Rajkumar, Theja Tulabandhula:
Provable Inductive Robust PCA via Iterative Hard Thresholding. UAI 2017 - [i3]U. N. Niranjan, Arun Rajkumar:
Inductive Pairwise Ranking: Going Beyond the n log(n) Barrier. CoRR abs/1702.02661 (2017) - [i2]Arun Rajkumar, Koyel Mukherjee, Theja Tulabandhula:
Learning to Partition using Score Based Compatibilities. CoRR abs/1703.07807 (2017) - [i1]U. N. Niranjan, Arun Rajkumar, Theja Tulabandhula:
Provable Inductive Robust PCA via Iterative Hard Thresholding. CoRR abs/1704.00367 (2017) - 2016
- [c7]Arun Rajkumar, Shivani Agarwal:
When can we rank well from comparisons of \(O(n\log(n))\) non-actively chosen pairs? COLT 2016: 1376-1401 - [c6]Himanshu S. Bhatt, Arun Rajkumar, Shourya Roy:
Multi-Source Iterative Adaptation for Cross-Domain Classification. IJCAI 2016: 3691-3697 - [c5]Siddartha Y. Ramamohan, Arun Rajkumar, Shivani Agarwal:
Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions. NIPS 2016: 1253-1261 - 2015
- [c4]Arun Rajkumar, Suprovat Ghoshal, Lek-Heng Lim, Shivani Agarwal:
Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top. ICML 2015: 665-673 - 2014
- [c3]Arun Rajkumar, Shivani Agarwal:
A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data. ICML 2014: 118-126 - [c2]Arun Rajkumar, Shivani Agarwal:
Online Decision-Making in General Combinatorial Spaces. NIPS 2014: 3482-3490 - 2012
- [c1]Arun Rajkumar, Shivani Agarwal:
A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification. AISTATS 2012: 933-941
Coauthor Index
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