Multi-Armed Bandit Algorithms for Crowdsourcing Systems with Online Estimation of Workers' Ability. - Anshuka Rangi; Massimo Franceschetti (AAMAS, 2018)

Consensus-Based Chernoff Test in Sensor Networks. - Anshuka Rangi; Massimo Franceschetti; Stefano Maranò 001 (CDC, 2018)

Decentralized Chernoff Test in Sensor Networks. - Anshuka Rangi; Massimo Franceschetti; Stefano Maranò 001 (ISIT, 2018)

Online learning with feedback graphs and switching costs. - Anshuka Rangi; Massimo Franceschetti (AISTATS, 2019)

Unifying the Stochastic and the Adversarial Bandits with Knapsack. - Anshuka Rangi; Massimo Franceschetti; Long Tran-Thanh (IJCAI, 2019)

Towards a Non-Stochastic Information Theory. - Anshuka Rangi; Massimo Franceschetti (ISIT, 2019)

Channel Coding Theorems in Non-stochastic Information Theory. - Anshuka Rangi; Massimo Franceschetti (ISIT, 2021)

Learning based attacks in Cyber Physical Systems: Exploration, Detection, and Control Cost trade-offs. - Anshuka Rangi; Mohammad Javad Khojasteh; Massimo Franceschetti (L4DC, 2021)

Sequential Choice Bandits with Feedback for Personalizing users' experience. - Anshuka Rangi; Massimo Franceschetti; Long Tran-Thanh (CoRR, 2021)

Secure-UCB: Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification. - Anshuka Rangi; Long Tran-Thanh; Haifeng Xu; Massimo Franceschetti (CoRR, 2021)

Distributed Chernoff Test: Optimal Decision Systems Over Networks. - Anshuka Rangi; Massimo Franceschetti; Stefano Maranò 001 (IEEE Trans. Inf. Theory, 2021)

Online Learning and Decision Making with Partial Information, a feedback perspective. - Anshuka Rangi (2021)

Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification. - Anshuka Rangi; Long Tran-Thanh; Haifeng Xu; Massimo Franceschetti (AAAI, 2022)

Understanding the Limits of Poisoning Attacks in Episodic Reinforcement Learning. - Anshuka Rangi; Haifeng Xu; Long Tran-Thanh; Massimo Franceschetti (IJCAI, 2022)

Multi-Player Bandits Robust to Adversarial Collisions. - Shivakumar Mahesh; Anshuka Rangi; Haifeng Xu; Long Tran-Thanh (CoRR, 2022)

Towards Sequential Counterfactual Learning to Rank. - Tesi Xiao; Branislav Kveton; Sumeet Katariya; Tanmay Gangwani; Anshuka Rangi (SIGIR-AP, 2023)

Selective Uncertainty Propagation in Offline RL. - Sanath Kumar Krishnamurthy; Tanmay Gangwani; Sumeet Katariya; Branislav Kveton; Anshuka Rangi (CoRR, 2023)

Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient Flow. - Yinuo Ren; Tesi Xiao; Tanmay Gangwani; Anshuka Rangi; Holakou Rahmanian; Lexing Ying; Subhajit Sanyal (AISTATS, 2024)

Attacking Multi-Player Bandits and How to Robustify Them. - Shivakumar Mahesh; Anshuka Rangi; Haifeng Xu; Long Tran-Thanh (AAMAS, 2024)

Selective Uncertainty Propagation in Offline RL. - Sanath Kumar Krishnamurthy; Tanmay Gangwani; Sumeet Katariya; Branislav Kveton; Shrey Modi; Anshuka Rangi (AAAI, 2025)