728 citations · 1.7k across the 39 of their papers we have counts for
9 papers · 1 filter
Discovery and Separation of Features for Invariant Representation Learning
Ayush Jaiswal, Rob Brekelmans, Daniel Moyer +3
Supervised machine learning models often associate irrelevant nuisance factors with the prediction target, which hurts generalization. We propose a framework for training robust ne…
Invariant Representations through Adversarial Forgetting
Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg +2
We propose a novel approach to achieving invariance for deep neural networks in the form of inducing amnesia to unwanted factors of data through a new adversarial forgetting mechan…
The Woman Worked as a Babysitter: On Biases in Language Generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan +1
We present a systematic study of biases in natural language generation (NLG) by analyzing text generated from prompts that contain mentions of different demographic groups. In this…
Report of 2017 NSF Workshop on Multimedia Challenges, Opportunities and Research Roadmaps
Shih-Fu Chang, Alex Hauptmann, Louis-Philippe Morency +18
With the transformative technologies and the rapidly changing global R&D landscape, the multimedia and multimodal community is now faced with many new opportunities and uncertainti…
NIESR: Nuisance Invariant End-to-end Speech Recognition
I-Hung Hsu, Ayush Jaiswal, Premkumar Natarajan
Deep neural network models for speech recognition have achieved great success recently, but they can learn incorrect associations between the target and nuisance factors of speech…
Recurrent Convolutional Strategies for Face Manipulation Detection in Videos
Ekraam Sabir, Jiaxin Cheng, Ayush Jaiswal +3
The spread of misinformation through synthetically generated yet realistic images and videos has become a significant problem, calling for robust manipulation detection methods. De…
Unified Adversarial Invariance
Ayush Jaiswal, Yue Wu, Wael AbdAlmageed +1
We present a unified invariance framework for supervised neural networks that can induce independence to nuisance factors of data without using any nuisance annotations, but can ad…
QATM: Quality-Aware Template Matching For Deep Learning
Jiaxin Cheng, Yue Wu, Wael Abd-Almageed +1
Finding a template in a search image is one of the core problems many computer vision, such as semantic image semantic, image-to-GPS verification \etc. We propose a novel quality-a…
AIRD: Adversarial Learning Framework for Image Repurposing Detection
Ayush Jaiswal, Yue Wu, Wael AbdAlmageed +2
Image repurposing is a commonly used method for spreading misinformation on social media and online forums, which involves publishing untampered images with modified metadata to cr…