Title:Â Dot-Product Proofs Speaker: Prahladh Harsha (TIFR Mumbai):Â Details: July 28 (Monday) | 11:30 AM | Bharti 404 Abstract:Â A dot-product proof is a simple probabilistic proof system in which the verifier decides whether to accept an input vector based on a single linear combination of the entries of the input and a proof vector. In this… Read More »Dot-Product Proofs by Prahladh Harsha
Abstract: Aggregating multiple input rankings over a set of candidates to generate a consensus ranking is one of the fundamental ranking problems, having many applications in social choice theory, hiring, college admission, web search, and databases. However, the optimal consensus ranking might be biased against any individual candidate or candidates belonging to certain marginalized communities… Read More »Rank Aggregation and Fairness by Diptarka Chakraborty
Title: Multiturn Evals (and RL) for LLMs Details: 8th August, 12 pm, SIT001 Abstract:Â LLMs often fail at multi-step tasks requiring memory and strategic planning, a gap not captured by traditional single-turn evals. To address this, we've developed a suite of human and automated evals that stress test Gemini on these capabilities. This talk will cover… Read More »Multiturn Evals (and RL) for LLMs by Kartikeya Badola
Title:Â Explainable AI for Malware Analysis Abstract:Â In recent years, explainable artificial intelligence (XAI) has become a critical component of ensuring transparency and trust in machine learning systems, particularly in high-stakes domains like cybersecurity. This talk will begin with a basic introduction to XAI, highlighting its importance in understanding model decisions, especially in the context of… Read More »Explainable AI for Malware Analysis by Mohd Saqib
Speaker: Akash Kumar (Ruhr University Bochum) Details: Tue, 12 Aug, 3:30 PM, SIT 001 Abstract: The widespread adoption of Artificial intelligence and Machine Learning (AI/ML) models across various fields, such as healthcare, autonomous vehicles, smart agriculture, and industrial automation, has led to a growing demand for efficient and scalable AI/ML solutions. However, as AI/ML algorithms… Read More »Enabling Energy-efficient AI Computing: Leveraging Application-specific Approximations by Akash Kumar
Title: A brief survey of quantum numerical algorithms Speaker: Prof. Pranav Singh Details: August 14 (Thursday) | 12(noon)-1 PM | Bharti 501 Abstract: Quantum Numerical Algorithms (QNA) encompass a broad class of techniques including quantum numerical linear algebra (QNLA), quantum optimization, quantum variational algorithms (QVA), quantum machine learning (QML), and Hamiltonian simulation (HS). These areas… Read More »A brief survey of quantum numerical algorithms by Pranav Singh
Abstract:Â In this talk, we consider the Hospitals/Residents (HR) problem in the presence of ties in preference lists of hospitals. Among the three notions of stability, viz. weak, strong, and super stability, we focus on strong stability. Strong stability is appealing both theoretically and practically; however, its existence is not guaranteed. Our objective is to optimally… Read More »Optimal Capacity Modification for Stable Matchings with Ties by Dr. Keshav Ranjan
