145 citations · 269 across the 15 of their papers we have counts for
16 papers
Value bounds and Convergence Analysis for Averages of LRP attributions
Alexander Binder, Nastaran Takmil-Homayouni, Urun Dogan
We analyze numerical properties of Layer-wise relevance propagation (LRP)-type attribution methods by representing them as a product of modified gradient matrices. This representat…
Offline RL With Resource Constrained Online Deployment
Jayanth Reddy Regatti, Aniket Anand Deshmukh, Frank Cheng +3
Offline reinforcement learning is used to train policies in scenarios where real-time access to the environment is expensive or impossible. As a natural consequence of these harsh…
Zero Shot Domain Generalization
Udit Maniyar, Joseph K J, Aniket Anand Deshmukh +2
Standard supervised learning setting assumes that training data and test data come from the same distribution (domain). Domain generalization (DG) methods try to learn a model that…
Self-Supervised Contextual Bandits in Computer Vision
Aniket Anand Deshmukh, Abhimanu Kumar, Levi Boyles +3
Contextual bandits are a common problem faced by machine learning practitioners in domains as diverse as hypothesis testing to product recommendations. There have been a lot of app…
Data Transformation Insights in Self-supervision with Clustering Tasks
Abhimanu Kumar, Aniket Anand Deshmukh, Urun Dogan +2
Self-supervision is key to extending use of deep learning for label scarce domains. For most of self-supervised approaches data transformations play an important role. However, up…
Label-similarity Curriculum Learning
Urun Dogan, Aniket Anand Deshmukh, Marcin Machura +1
Curriculum learning can improve neural network training by guiding the optimization to desirable optima. We propose a novel curriculum learning approach for image classification th…