Synapse August 2024

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Synapse

Monthly Newsletter from CNI

Issue - August 2024

Join us at the upcoming talk on "Random Separating Hyperplane Theorem and

Learning Polytopes" by Prof. Amit Kumar, IIT Delhi on 06/08/2024

Join us at the upcoming talk on "Codes for (Un)Expected Loads" by Prof. Emina

Soljanin, Distinguished Professor, Rutgers University on 12/08/2024.

What’s cooking at CNI?

End of Academic Session at CNI: Research Highlights

The 2024 academic session at the Centre for Networked Intelligence (CNI) saw students working across a wide spectrum of problems in networked systems, learning, and security. Topics this year included task-oriented communication strategies, mean-field games on sparse graphs, and Bayesian methods for rate adaptation in wireless networks. Students also explored scheduling algorithms for heterogeneous systems, pricing in multi-agent systems, and strategic decision-making models. Several projects addressed societal impact areas such as AI-driven oral cancer screening and privacy-preserving authentication in IoT platforms.

On the systems side, work was carried out on modeling power grid vulnerabilities, digital twins for battery networks, and fairness in Wi-Fi networks.

A full list of projects is available at: cni.iisc.ac.in/highlights

Past Events

Average Reward Markov Decision Process

In this talk, Prof. Vaneet Aggarwal explored infinite-horizon average-reward MDPs with a focus on regret guarantees for policy gradient-based algorithms. He discussed a novel gradient estimation technique with sublinear regret, and an efficient momentum-based method with improved regret. A strategy to reduce dependence on mixing time was also presented.

Designing Robust Algorithms for Data Streams that Might be Adversarially Generated

In this talk, Prof. Amit Chakrabarti introduced adversarially robust streaming algorithms, designed to handle feedback-driven data streams while ensuring correctness. Two recent results were discussed: one on the Missing Item Finding (MIF) problem, showing how space complexity depends on the randomness model, and another on graph coloring in streaming settings, where the achievable color budget is similarly impacted.

Learning in the Presence of Strategy

In this talk, Prof. Ganesh Ghalme explored learning-based decision-making systems in strategic settings, where humans may manipulate inputs or be influenced by curated outputs. Two frameworks were presented: strategic classification, where agents game the system, and strategic representation, where the system shapes agent behavior.

Leveraging WiFi for Robust and Resource-Efficient SLAM

In this talk, Aditya Arun presented a real-time SLAM system for indoor robots using WiFi radios as camera-like sensors, offering robustness to perceptual aliasing and dynamic visual conditions. Built with off-the-shelf components, the system was evaluated over 1500 m across three indoor environments. WiFi-based sensing yielded a 6X improvement over odometry and significantly reduced compute and memory usage compared to leading Visual and LiDAR SLAM systems

Online Learning for Hierarchical Inference

In this talk, Prof. Sharayu Moharir discussed Hierarchical Inference (HI) for efficient distributed inference between edge devices and cloud servers. The focus was on learning optimal thresholds for offloading predictions based on confidence metrics. New algorithms with sub-linear regret were proposed, offering significantly lower runtime and comparable performance, as demonstrated through experiments on Raspberry Pi.

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Centre for Networked Intelligence · Indian Institute of Science · Bangalore, Karnataka 560012 · India

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