3 papers
cs.LG2021
Do Input Gradients Highlight Discriminative Features?
Harshay Shah, Prateek Jain, Praneeth Netrapalli
Post-hoc gradient-based interpretability methods [Simonyan et al., 2013, Smilkov et al., 2017] that provide instance-specific explanations of model predictions are often based on a…
cs.LG2020
The Pitfalls of Simplicity Bias in Neural Networks
Harshay Shah, Kaustav Tamuly, Aditi Raghunathan +2
Several works have proposed Simplicity Bias (SB)---the tendency of standard training procedures such as Stochastic Gradient Descent (SGD) to find simple models---to justify why neu…
cs.LG2018
Number of Connected Components in a Graph: Estimation via Counting Patterns
Ashish Khetan, Harshay Shah, Sewoong Oh
Due to the limited resources and the scale of the graphs in modern datasets, we often get to observe a sampled subgraph of a larger original graph of interest, whether it is the wo…