1 citations · 1 across the 1 of their papers we have counts for
6 papers
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…
Is Ordered Weighted Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR
Pin-Yu Chen, Bhanukiran Vinzamuri, Sijia Liu
Many state-of-the-art machine learning models such as deep neural networks have recently shown to be vulnerable to adversarial perturbations, especially in classification tasks. Mo…
Structure Learning from Time Series with False Discovery Control
Bernat Guillen Pegueroles, Bhanukiran Vinzamuri, Karthikeyan Shanmugam +3
We consider the Granger causal structure learning problem from time series data. Granger causal algorithms predict a 'Granger causal effect' between two variables by testing if pre…