Exploiting Submodular Value Functions for Faster Dynamic Sensor Selection. - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek (AAAI, 2015)

Probably Approximately Correct Greedy Maximization: (Extended Abstract). - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek (AAMAS, 2016)

PAC Greedy Maximization with Efficient Bounds on Information Gain for Sensor Selection. - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek (IJCAI, 2016)

Probably Approximately Correct Greedy Maximization. - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek (CoRR, 2016)

Real-Time Resource Allocation for Tracking Systems. - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek; Henri Bouma (UAI, 2017)

Exploiting submodular value functions for scaling up active perception. - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek; Matthijs T. J. Spaan (Auton. Robots, 2018)

Maximizing Information Gain in Partially Observable Environments via Prediction Rewards. - Yash Satsangi; Sungsu Lim; Shimon Whiteson; Frans A. Oliehoek; Martha White (AAMAS, 2020)

Maximizing Information Gain in Partially Observable Environments via Prediction Reward. - Yash Satsangi; Sungsu Lim; Shimon Whiteson; Frans A. Oliehoek; Martha White (CoRR, 2020)

Useful Policy Invariant Shaping from Arbitrary Advice. - Paniz Behboudian; Yash Satsangi; Matthew E. Taylor; Anna Harutyunyan; Michael Bowling (CoRR, 2020)

Learning to Be Cautious. - Montaser Mohammedalamen; Dustin Morrill; Alexander Sieusahai; Yash Satsangi; Michael Bowling (CoRR, 2021)

Ledgit: A Service to Diagnose Illicit Addresses on Blockchain using Multi-modal Unsupervised Learning. - Xiaoying Zhi; Yash Satsangi; Sean J. Moran; Shaltiel Eloul (CIKM, 2022)

Topical: Learning Repository Embeddings from Source Code using Attention. - Agathe Lherondelle; Yash Satsangi; Fran Silavong; Shaltiel Eloul; Sean J. Moran (CoRR, 2022)

Policy invariant explicit shaping: an efficient alternative to reward shaping. - Paniz Behboudian; Yash Satsangi; Matthew E. Taylor; Anna Harutyunyan; Michael Bowling (Neural Comput. Appl., 2022)

Bandit-Based Policy Invariant Explicit Shaping for Incorporating External Advice in Reinforcement Learning. - Yash Satsangi; Paniz Behboudian (CoRR, 2023)

An Unsupervised Method for Estimating Class Separability of Datasets with Application to LLMs Fine-Tuning. - Najah Ghalyan; Kostis Gourgoulias; Yash Satsangi; Sean J. Moran; Maxime Labonne; Joseph Sabelja (CoRR, 2023)

Absolute Variation Distance: An Inversion Attack Evaluation Metric for Federated Learning. - Georgios Papadopoulos 007; Yash Satsangi; Shaltiel Eloul; Marco Pistoia (ECIR (4), 2024)

Ranking Distance Metric for Privacy Budget in Distributed Learning of Finite Embedding Data. - Georgios Papadopoulos 007; Yash Satsangi; Shaltiel Eloul; Marco Pistoia (ECIR (4), 2024)

Topical: Automatic Repository Tagging using Attention on Hybrid Code Embeddings. - Agathe Lherondelle; Varun Babbar; Yash Satsangi; Fran Silavong; Shaltiel Eloul; Sean J. Moran (FinanSE@ICSE, 2024)

Estimating class separability of text embeddings with persistent homology. - Kostis Gourgoulias; Najah Ghalyan; Maxime Labonne; Yash Satsangi; Sean J. Moran; Joseph Sabelja (Trans. Mach. Learn. Res., 2024)

Private, Auditable, and Distributed Ledger for Financial Institutes. - Shaltiel Eloul; Yash Satsangi; Yeoh Wei Zhu; Omar Amer; Georgios Papadopoulos 007; Marco Pistoia (CoRR, 2025)

Applications of Certified Randomness. - Omar Amer; Shouvanik Chakrabarti; Kaushik Chakraborty; Shaltiel Eloul; Niraj Kumar 005; Charles Lim; Minzhao Liu; Pradeep Niroula; Yash Satsangi; Ruslan Shaydulin; Marco Pistoia (CoRR, 2025)

A Numerical Gradient Inversion Attack in Variational Quantum Neural-Networks. - Georgios Papadopoulos 007; Shaltiel Eloul; Yash Satsangi; Jamie Heredge; Niraj Kumar 005; Chun-Fu Chen 001; Marco Pistoia (CoRR, 2025)