activity
20162025
most citedIA-RED: Interpretability-Aware Redundancy Reduction for Vision Transformers

68 citations · 278 across the 32 of their papers we have counts for

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Showing 2020Show all

10 papers · 1 filter

cs.LG20201 cited

A Maximal Correlation Approach to Imposing Fairness in Machine Learning

Joshua Lee, Yuheng Bu, Prasanna Sattigeri +4

As machine learning algorithms grow in popularity and diversify to many industries, ethical and legal concerns regarding their fairness have become increasingly relevant. We explor…

cs.CV20202 cited

Large Scale Neural Architecture Search with Polyharmonic Splines

Ulrich Finkler, Michele Merler, Rameswar Panda +8

Neural Architecture Search (NAS) is a powerful tool to automatically design deep neural networks for many tasks, including image classification. Due to the significant computationa…

cs.CV2020

Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition

Chun-Fu Chen, Rameswar Panda, Kandan Ramakrishnan +4

In recent years, a number of approaches based on 2D or 3D convolutional neural networks (CNN) have emerged for video action recognition, achieving state-of-the-art results on sever…

cs.CV20203 cited

Measurement-driven Security Analysis of Imperceptible Impersonation Attacks

Shasha Li, Karim Khalil, Rameswar Panda +4

The emergence of Internet of Things (IoT) brings about new security challenges at the intersection of cyber and physical spaces. One prime example is the vulnerability of Face Reco…

cs.CV2020

Adversarial Knowledge Transfer from Unlabeled Data

Akash Gupta, Rameswar Panda, Sujoy Paul +2

While machine learning approaches to visual recognition offer great promise, most of the existing methods rely heavily on the availability of large quantities of labeled training d…

cs.CV2020

Mitigating Dataset Imbalance via Joint Generation and Classification

Aadarsh Sahoo, Ankit Singh, Rameswar Panda +2

Supervised deep learning methods are enjoying enormous success in many practical applications of computer vision and have the potential to revolutionize robotics. However, the mark…