Aadirupa Saha

According to our database, Aadirupa Saha authored at least 49 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

DP-Dueling: Learning from Preference Feedback without Compromising User Privacy.

Aadirupa Saha, Hilal Asi

CoRR, 2024

Stop Relying on No-Choice and Do not Repeat the Moves: Optimal, Efficient and Practical Algorithms for Assortment Optimization.

Aadirupa Saha, Pierre Gaillard

CoRR, 2024

2023

Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources.

Rohan Deb, Aadirupa Saha

CoRR, 2023

Faster Convergence with Multiway Preferences.

Aadirupa Saha, Vitaly Feldman, Tomer Koren, Yishay Mansour

CoRR, 2023

Federated Online and Bandit Convex Optimization.

Kumar Kshitij Patel, Lingxiao Wang, Aadirupa Saha, Nati Sebro

CoRR, 2023

Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation.

Thomas Kleine Buening, Aadirupa Saha, Christos Dimitrakakis, Haifeng Xu

CoRR, 2023

Dueling Optimization with a Monotone Adversary.

Avrim Blum, Meghal Gupta, Gene Li, Naren Sarayu Manoj, Aadirupa Saha, Yuanyuan Yang

CoRR, 2023

On the Vulnerability of Fairness Constrained Learning to Malicious Noise.

Avrim Blum, Princewill Okoroafor, Aadirupa Saha, Kevin Stangl

CoRR, 2023

Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling.

Aadirupa Saha, Branislav Kveton

CoRR, 2023

Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback.

Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R. Walter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Federated Online and Bandit Convex Optimization.

Kumar Kshitij Patel, Lingxiao Wang, Aadirupa Saha, Nathan Srebro

Proceedings of the International Conference on Machine Learning, 2023

Dueling RL: Reinforcement Learning with Trajectory Preferences.

Aadirupa Saha, Aldo Pacchiano, Jonathan Lee

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

One Arrow, Two Kills: A Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits.

Pierre Gaillard, Aadirupa Saha, Soham Dan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

ANACONDA: An Improved Dynamic Regret Algorithm for Adaptive Non-Stationary Dueling Bandits.

Thomas Kleine Buening, Aadirupa Saha

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

One Arrow, Two Kills: An Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits.

Pierre Gaillard, Aadirupa Saha, Soham Dan

CoRR, 2022

Dueling Convex Optimization with General Preferences.

Aadirupa Saha, Tomer Koren, Yishay Mansour

CoRR, 2022

Versatile Dueling Bandits: Best-of-both-World Analyses for Online Learning from Preferences.

Aadirupa Saha, Pierre Gaillard

CoRR, 2022

Optimal and Efficient Dynamic Regret Algorithms for Non-Stationary Dueling Bandits.

Aadirupa Saha, Shubham Gupta

Proceedings of the International Conference on Machine Learning, 2022

Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences.

Aadirupa Saha, Pierre Gaillard

Proceedings of the International Conference on Machine Learning, 2022

Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models.

Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier

Proceedings of the International Conference on Machine Learning, 2022

Efficient and Optimal Algorithms for Contextual Dueling Bandits under Realizability.

Aadirupa Saha, Akshay Krishnamurthy

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits.

Aadirupa Saha, Suprovat Ghoshal

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

A Sketch Based Game Theoretic Approach to Detect Anomalous Dense Sub-Communities in Large Data Streams.

Prateek Chanda, Aadirupa Saha

CoRR, 2021

Pure Exploration with Structured Preference Feedback.

Shubham Gupta, Aadirupa Saha, Sumeet Katariya

CoRR, 2021

Strategically efficient exploration in competitive multi-agent reinforcement learning.

Robert Tyler Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Dueling Bandits with Adversarial Sleeping.

Aadirupa Saha, Pierre Gaillard

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Optimal Algorithms for Stochastic Contextual Preference Bandits.

Aadirupa Saha

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization.

Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain

Proceedings of the 38th International Conference on Machine Learning, 2021

Dueling Convex Optimization.

Aadirupa Saha, Tomer Koren, Yishay Mansour

Proceedings of the 38th International Conference on Machine Learning, 2021

Adversarial Dueling Bandits.

Aadirupa Saha, Tomer Koren, Yishay Mansour

Proceedings of the 38th International Conference on Machine Learning, 2021

Confidence-Budget Matching for Sequential Budgeted Learning.

Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Improved Sleeping Bandits with Stochastic Actions Sets and Adversarial Rewards.

Aadirupa Saha, Pierre Gaillard, Michal Valko

CoRR, 2020

Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards.

Aadirupa Saha, Pierre Gaillard, Michal Valko

Proceedings of the 37th International Conference on Machine Learning, 2020

From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model.

Aadirupa Saha, Aditya Gopalan

Proceedings of the 37th International Conference on Machine Learning, 2020

Best-item Learning in Random Utility Models with Subset Choices.

Aadirupa Saha, Aditya Gopalan

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Polytime Decomposition of Generalized Submodular Base Polytopes with Efficient Sampling.

Aadirupa Saha

Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019

Regret Minimisation in Multinomial Logit Bandits.

Aadirupa Saha, Aditya Gopalan

CoRR, 2019

Be Greedy: How Chromatic Number meets Regret Minimization in Graph Bandits.

Aadirupa Saha, Shreyas Sheshadri, Chiranjib Bhattacharyya

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Combinatorial Bandits with Relative Feedback.

Aadirupa Saha, Aditya Gopalan

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

PAC Battling Bandits in the Plackett-Luce Model.

Aadirupa Saha, Aditya Gopalan

Proceedings of the Algorithmic Learning Theory, 2019

Active Ranking with Subset-wise Preferences.

Aadirupa Saha, Aditya Gopalan

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

How Many Pairwise Preferences Do We Need to Rank a Graph Consistently?

Aadirupa Saha, Rakesh Shivanna, Chiranjib Bhattacharyya

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

PAC-Battling Bandits with Plackett-Luce: Tradeoff between Sample Complexity and Subset Size.

Aditya Gopalan, Aadirupa Saha

CoRR, 2018

Battle of Bandits.

Aadirupa Saha, Aditya Gopalan

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Online Learning for Structured Loss Spaces.

Siddharth Barman, Aditya Gopalan, Aadirupa Saha

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2015

Consistent Multiclass Algorithms for Complex Performance Measures.

Harikrishna Narasimhan, Harish G. Ramaswamy, Aadirupa Saha, Shivani Agarwal

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Learning Score Systems for Patient Mortality Prediction in Intensive Care Units via Orthogonal Matching Pursuit.

Aadirupa Saha, Chandrahas Dewangan, Harikrishna Narasimhan, Sriram Sampath, Shivani Agarwal

Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

2013

Energy Saving Replay Attack Prevention in Clustered Wireless Sensor Networks.

Amrita Ghosal, Aadirupa Saha, Sipra Das Bit

Proceedings of the Intelligence and Security Informatics - Pacific Asia Workshop, 2013

2011

Energy-Balancing and Lifetime Enhancement of Wireless Sensor Network with Archimedes Spiral.

Subir Halder, Amrita Ghosal, Aadirupa Saha, DasBit Sipra

Proceedings of the Ubiquitous Intelligence and Computing - 8th International Conference, 2011