20 citations · 51 across the 11 of their papers we have counts for
6 papers · 1 filter
BLUR: A Bi-Level Optimization Approach for LLM Unlearning
Hadi Reisizadeh, Jinghan Jia, Zhiqi Bu +6
Enabling large language models (LLMs) to unlearn knowledge and capabilities acquired during training has proven vital for ensuring compliance with data regulations and promoting et…
Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate
Zhiqi Bu, Xiaomeng Jin, Bhanukiran Vinzamuri +4
Machine unlearning has been used to remove unwanted knowledge acquired by large language models (LLMs). In this paper, we examine machine unlearning from an optimization perspectiv…
Fair Representation Learning using Interpolation Enabled Disentanglement
Akshita Jha, Bhanukiran Vinzamuri, Chandan K. Reddy
With the growing interest in the machine learning community to solve real-world problems, it has become crucial to uncover the hidden reasoning behind their decisions by focusing o…
Model Agnostic Multilevel Explanations
Karthikeyan Natesan Ramamurthy, Bhanukiran Vinzamuri, Yunfeng Zhang +1
In recent years, post-hoc local instance-level and global dataset-level explainability of black-box models has received a lot of attention. Much less attention has been given to ob…
Unsupervised Anomaly Detection with Adversarial Mirrored AutoEncoders
Gowthami Somepalli, Yexin Wu, Yogesh Balaji +2
Detecting out of distribution (OOD) samples is of paramount importance in all Machine Learning applications. Deep generative modeling has emerged as a dominant paradigm to model co…
Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines
Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri +4
The dearth of prescribing guidelines for physicians is one key driver of the current opioid epidemic in the United States. In this work, we analyze medical and pharmaceutical claim…