Centre for Networked Intelligence

Dear All, Networks Seminar, supported by the Centre for Networked Intelligence, is a technical discussion forum in topics including but not limited to computer networks, machine learning, signal processing, and information theory. The seminar series has a webpage hosted at https://cni.iisc.ac.in/seminars/. You are invited to the following seminar held as part of this series. Title: Nash Regret and Beyond: Optimal Fairness Guarantees in Bandit Problems Speaker: Prof. Sayak Ray Chowdhury, Assistant Professor, IIT Kanpur Time: 4:00 PM - 5:00 PM (IST) Date: 10 August 2026 Venue: GJ Hall and Online on Zoom Tea/Coffee: 5:00 PM Zoom link: https://us06web.zoom.us/j/83388976389?pwd=XcpO3GhLxsR14a7SVbPx33HQQa1jbt.1 Zoom Meeting ID: 833 8897 6389, Pass Code: NSSIISc YouTube: https://www.youtube.com/watch?v=Wu8MynsrO0Q&list=PLNN9TCnjABcY5RBvFXAghzQ6HMsNX8GeF Webpage Link: https://cni.iisc.ac.in/seminars/2026-08-10/ <https://cni.iisc.ac.in/seminars/2026-08-10/> Abstract: Traditional regret minimization in multi-armed bandits focuses on maximizing cumulative reward, often overlooking fairness across individuals receiving outcomes. Motivated by applications such as clinical trials and resource allocation, Nash regret has been proposed as a fairness-aware metric based on the geometric mean of rewards. In this talk, I will present recent results showing that near-optimal Nash regret can be achieved using simple and general bandit algorithms under mild assumptions in stochastic bandits, along with extensions to a broader class of power-mean fairness objectives. I will then discuss fairness in linear bandits, where we obtain the first order-optimal Nash regret bounds in dimension and introduce a generic meta-algorithm that converts standard linear bandit methods into fairness-aware versions with provable guarantees. Empirical results demonstrate consistent improvements over existing approaches. Overall, the work highlights that fairness can be incorporated into bandit learning without sacrificing statistical efficiency. Bio: Sayak Ray Chowdhury is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur. His research focuses on sequential decision making under uncertainty, including multi-armed bandits, reinforcement learning, and language model alignment, as well as on privacy and fairness in ML. Prior to joining IIT Kanpur, he was a Postdoctoral Researcher at Microsoft Research India and Boston University. He received his Ph.D. from the Indian Institute of Science (IISc), Bangalore. He is a recipient of the INAE Young Associate award from the Indian National Academy of Engineering. More Details: https://sites.google.com/view/sayakraychowdhury/home ALL ARE WELCOME. Thank you, CNI Seminar Series Organizing Committee.

Dear All, Networks Seminar, supported by the Centre for Networked Intelligence, is a technical discussion forum in topics including but not limited to computer networks, machine learning, signal processing, and information theory. The seminar series has a webpage hosted at https://cni.iisc.ac.in/seminars/. You are invited to the following seminar held as part of this series. Title: (Quantum) Codes and Coorrelations Speaker: Prof. Emina Soljanin, Distinguished Professor, Rutgers University Time: 5:00 PM - 6:00 PM (IST) Date: 11 August 2026 Venue: GJ Hall and Online on Zoom Tea/Coffee: 6:00 PM Zoom link: https://us06web.zoom.us/j/83388976389?pwd=XcpO3GhLxsR14a7SVbPx33HQQa1jbt.1 Zoom Meeting ID: 833 8897 6389, Pass Code: NSSIISc YouTube: https://www.youtube.com/watch?v=Wu8MynsrO0Q&list=PLNN9TCnjABcY5RBvFXAghzQ6HMsNX8GeF Webpage Link: https://cni.iisc.ac.in/seminars/2026-08-11/ <https://cni.iisc.ac.in/seminars/2026-08-11/> Abstract: We study games in which a referee poses a guessing challenge, and two or more players aim to coordinate their guesses to meet a joint winning condition. The players can devise a joint strategy in preparation for the game, but they cannot communicate once the game starts. Classic games include various hat-color-guessing puzzles where players use codes to correlate their guesses. Such games provide simple, illustrative examples to help appreciate various notions in coding theory, telecommunications, combinatorics, and communication complexity. Quantum guessing games are an effective modern tool for studying the kinds of correlations that are possible when players share entangled quantum states. They are of interest to both the foundations of quantum mechanics and envisioned quantum computing applications, e.g., cryptography. This talk discusses codes and entanglement as coordination tools and correlation-building devices in several multi-player games. Bio: Emina Soljanin is a Distinguished Professor of Electrical and Computer Engineering at Rutgers. Before moving to Rutgers in January 2016, she was a (Distinguished) Member of Technical Staff for 21 years in the Mathematical Sciences Research Center of Bell Labs. Her interests and expertise are broad, currently spanning distributed computing and quantum information science. She is an IEEE Fellow, an outstanding alumnus of the Texas A&M School of Engineering, the 2011 Padovani Lecturer, a 2016/17 Distinguished Lecturer, and the 2019 IEEE Information Theory Society President. In 2023, Emina received the IEEE Information Theory Society Aaron D. Wyner Distinguished Service Award and the Mrs. Urmila Agrawal Distinguished Visiting Chair Professorship at the Indian Institute of Science. More Details: https://ece.rutgers.edu/emina-soljanin ALL ARE WELCOME. Thank you, CNI Seminar Series Organizing Committee.

Dear All, Networks Seminar, supported by the Centre for Networked Intelligence, is a technical discussion forum in topics including but not limited to computer networks, machine learning, signal processing, and information theory. The seminar series has a webpage hosted at https://cni.iisc.ac.in/seminars/. You are invited to the following seminar held as part of this series. Title: Distributed Online Stochastic Optimization with Myopic Agents Speaker: Prof. Ankur Mani, Affiliated Faculty, University of Minnesota Time: 5:00 PM - 6:00 PM (IST) Date: 13 August 2026 Venue: GJ Hall and Online on Zoom Tea/Coffee: 6:00 PM Zoom link: https://us06web.zoom.us/j/83388976389?pwd=XcpO3GhLxsR14a7SVbPx33HQQa1jbt.1 Zoom Meeting ID: 833 8897 6389, Pass Code: NSSIISc YouTube: https://www.youtube.com/watch?v=Wu8MynsrO0Q&list=PLNN9TCnjABcY5RBvFXAghzQ6HMsNX8GeF Webpage Link: https://cni.iisc.ac.in/seminars/2026-08-13/ <https://cni.iisc.ac.in/seminars/2026-08-13/> Abstract: Sequential decision making by a large set of myopic agents has gained significant attention over the past decade. In such settings, even a little amount of experimentation from a few agents would benefit all others but obtaining such experimentation could be challenging for a central planner. The academic literature has focused on mechanisms for promoting experimentation through monetary incentives and persuasion through careful information disclosure. We study simple controls that the central planner can use to coordinate experimentation. We consider a set of myopic agents that observe their own histories but not the histories of other agents. In a continuous-time stochastic multi-armed bandit model, the agents pick arms myopically and receive instantaneous rewards. Meanwhile, the central planner can observe the history of all agents. We consider a class of policies where the central planner is allowed to irrevocably remove arms. We show that an appropriately chosen policy within this class can generate the needed experimentation and match the regret bounds for a centralized problem thus mitigating the cost of decentralization. We also quantify the minimum number of agents that are needed for such a policy to be asymptotically optimal and the impact of the number of agents on the speed of learning. We then extend our study to online stochastic linear programs and characterize a geometric policy that mitigates the cost of decentralization and myopia. Bio: Ankur Mani is a visiting scholar at the University of Illinois Urbana-Champai, an affiliated faculty in the Industrial and Systems Engineering department at the University of Minnesota, Twin Cities, and the founder of Social Ripple Solutions. He received his Ph.D. in Media Arts and Science at the Massachusetts Institute of Technology and spent a year at the New York University, Stern School of Business and Microsoft Research. His research takes an interdisciplinary approach towards efficient design of infrastructure networks and collective decision making, with applications in sustainable production and consumption, rooted in social and economic sciences, operations research, and computer science. His research has appeared in several prominent venues (Management Science, Production and Operations Management, Nature Human Behavior, ACM Economics and Computation, Association for the Advancement of Artificial Intelligence, Proceedings of the IEEE, IEEE Transactions on Signal Processing and others) and received accolades within these disciplines (INFORMS, POMS, Aviation Applications Society, Net Institute). More Details: https://sites.google.com/umn.edu/amani ALL ARE WELCOME. Thank you, CNI Seminar Series Organizing Committee.