Published in IEEE Internation Symposium on Information Theory (ISIT), 2026, 2026
🎯 The principal aim of our work is to analyze such regret-tail behavior of optimal bandit algorithms in a relatively broader setting: policies that are optimized for generic families of reward distributions under significantly weaker structural assumptions
Recommended citation: https://arxiv.org/pdf/2604.14876
Published in 14th International Conference on Learning representations, 2025
🎯 The principal objective of this work is to propose a hypothesis testing framework for estimating the influnce of training data for a model prediction.
Recommended citation: https://arxiv.org/abs/2510.10510
Published in NeurIPS, 2024 Workshop on SafeGenAi, 2024
🎯 The principal objective of this work is to propose a machine unlearning methodology that can prevent the generation of outputs containing undesired features from a pre-trained diffusion model.
Recommended citation: https://openreview.net/pdf?id=B2wDjiED9V
Published in 41st Conference on Uncertainty in Artifical Intelligence (UAI,2025), 2024
🎯 The primary aim of this study is to propose a mathematical definition of forgetting in ML models and develop methodologies for forgetting specific undesired concepts from pre-trained classification models.
Recommended citation: https://openreview.net/pdf?id=2L7KQ4qbHi
Published in The 39th Annual AAAI Conference on Artificial Intelligence (AAAI,2025), 2024
🎯 The principal aim of this study is to formulate a methodology tailored for the purposeful elimination of information linked to a specific class of data from a pre-trained classification network.
Recommended citation: https://ojs.aaai.org/index.php/AAAI/article/view/32682
Published in IEEE Transactions on Artificial Intelligence (TAI,2024), 2023
🎯 The primary goal of this study is twofold: first, to elucidate the relationship between filtering and unlearning processes, and second, to formulate a methodology aimed at mitigating the display of undesirable outputs generated from models characterized as black-box systems.
Recommended citation: https://ieeexplore.ieee.org/abstract/document/10754629
Published in Transactions on Machine Learning Research (TMLR,2025), 2023
🎯 The objective of this work is to prevent the generation of outputs containing undesired features from a pre-trained GAN where the underlying training data set is inaccessible.
Recommended citation: https://arxiv.org/abs/2309.14054
Published in IEEE International Symposium on Devices Circuits and Systems (ISDCS), 2018
🎯 The objective of this project is to utilize a LASER INDUCED BREAKDOWN SPECTROGRAPHY (LIBS) instrument for soil mineral composition analysis in agriculture, facilitated by an Android-controlled platform.
Recommended citation: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8379684