LIST OF PUBLICATIONS

2023

• Abdul Bakey Mir, Arun Rajkumar: Learning from Pairwise Comparisons Under Preference Reversals, Workshop of Many Facets of Preference Based Learning, ICML 2023 

• Elisha Parhi, Arun Rajkumar: Distinguishing Feature Model for Learning From Pairwise Comparisons, Workshop of Many Facets of Preference Based Learning, ICML 2023 

• Utsav Dey, Lakshmi Narasimhan Theagarajan, Arun Rajkumar: Linearly Constrained and Structured Reinforcement Learning Algorithm for Wireless Link Adaptation, Workshop on Machine Learning for Wireless Communication, WiOpt 2023.

• Tushar Phule, Pragalbh Vashishtha and Arun Rajkumar: Active Learning with a Budget to Rank Candidates Rated by Disjoint Assessors, Workshop on online and adaptive recommender systems (OARS), KDD 2023 

• Sudha S,  Arun Rajkumar:  A Bandits Approach to Intelligent Tutoring Systems using Concept Evolution Estimation, DAI 2023

• K Vikas Mahendar, Chandrashekar L, Arun Rajkumar, Varun Seshadrinathan, Nithin Shivshankar : Deployment and Explanation of Deep Models for Endoscopy Video Classification, DAI 2023

• Pragalbh Vashishta, Hariprasad Gopalan, Arun Rajkumar, Valentine Barbender, Hans-Christian Schneider, Christoph Kirchlechner: Predicting Stress-Strain Curves from Indentation Curves using Deep Learning, DAI 2023

2022

• Arnhav Datar, Arun Rajkumar, John Augustine: Byzantine Spectral Ranking, Neurips 2022.

• Chadrashekar L, Amit Singh, Arun Rajkumar: Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality (Preprint)

• Arun Rajkumar, Abdul Bakey Mir and Vishnu Veerathu: A Theory of Tournament Representations, ICLR 2022 

• Athul M. A and Arun Rajkumar: Hyper-IMRANK: Ranking-based Influence Maximization for Hypergraphs To appear as a short research paper, CODS-COMAD 2022.

2021

• Vishnu Veerathu and Arun Rajkumar: On The Structure of Parametric Tournaments with Application to Ranking from Pairwise Comparisons, NeurIPS 2021.

• Dev Yashpal Sheth and Arun Rajkumar: PARWiS: Winner determination from Active Pairwise Comparisons under a Shoestring Budget, To appear as a full paper, ICDM 2021 | Preprint | Code.  (Was also presented at the Workshop of online and adaptive recommender systems (OARS), KDD 2021)

• Anant Shah and Arun Rajkumar: Sequential Ski Rental Problem, 20th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2021.

• Prateek Yadav and Arun Rajkumar: Rank Refinement: An Algorithmic Framework with Applications to Diversity Aware Influence Maximization, AAAI 2021 Workshop on Graphs and more Complex structures for Learning and Reasoning.

• Lokesh Kumar and Arun Rajkumar: DynamicGraphUCB - Personalized Recommendations on Evolving User Graphs, AAAI 2021 Workshop on Graphs and more Complex structures for Learning and Reasoning

2020

• Dev Yashpal Sheth and Arun Rajkumar: Active Ranking from Pairwise Comparisons with Dynamically Arriving Items and Voters, CODS-COMAD 2020.

2019

• Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar, Raman Sankaran:  Censored Semi Bandits: A Framework for Resource Allocation with Censored Feedback, NeurIPS, 2019. 

• Himanshu Sharad Bhatt, Shourya Roy, Arun Rajkumar, Sriranjani Ramakrishnan: Learning Transferable Feature Representations Using Neural Networks.  ACL, 2019. 

• Prateek Yadav, Madhav R Nimishakavi, Naganand Yadati, Shikhar Vashishth, Arun Rajkumar, Partha Talukdar: Lovász Convolutional Networks. In Proceedings of AISTATS, 2019.

2018 

• 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. In Proceedings of COMAD/CODS, 2018.

2017

• Arun Rajkumar, Koyel Mukherjee, Theja Tulabandhula: Learning to Partition using Score Based Compatibilities. In Proceedings of 16th confernce on Autonomous Agents and MultiAgent Systems, AAMAS 2017.

• U. N. Niranjan, Arun Rajkumar: Inductive Pairwise Ranking: Going Beyond the n log(n) Barrier. In Proceedings of 31st International Conference on Artificial Intelligence, AAAI 2017.

• U. N. Niranjan, Arun Rajkumar, Theja Tulabandhula: Provable Inductive Robust PCA via Iterative Hard Thresholding. In Proceedings of the 33rd conference on Uncertainity in Artificial Intelligence, UAI 2017.

2016

• Himanshu S. Bhatt, Arun Rajkumar, Shourya Roy: Multi-Source Iterative Adaptation for Cross-Domain Classification. In Proceedings of the 25th International Joint Conference on Artificial Intelligence, IJCAI 2016.

• Siddartha Y. Ramamohan, Arun Rajkumar, Shivani Agarwal: Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions. In Advances in Neural Information Processing Systems 29,NIPS 2016.

• Arun Rajkumar, Shivani Agarwal: When can we rank well from comparisons of O(nlog(n)) non-actively chosen pairs? In Proceedings of the 29th conference on learning theory, COLT 2016.

2015

• Arun Rajkumar, Suprovat Ghoshal, Lek-Heng Lim, Shivani Agarwal: Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top. In Proceedings of the 32nd International Conference on Machine Learning, ICML 2015.

2014

• Arun Rajkumar, Shivani Agarwal: A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data. In Proceedings of the 31st International Conference on Machine Learning, ICML 2014.

• Arun Rajkumar, Shivani Agarwal: Online Decision-Making in General Combinatorial Spaces. In Advances in Neural Information Processing Systems 27, NIPS 2014

Before 2014

• Arun Rajkumar, Shivani Agarwal: A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification. In Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2012.

• Arun Rajkumar, Suresh V, C.E. Veni Madhavan, M. Narasimha Murthy: On Finding the Natural Number of Topics with Latent Dirichlet Allocation: Some Observations. In Proceedings of the 14th Pacific-Asia Conference on Knowledge Discovery in Data Mining, PAKDD 2010.