4 citations · 8 across the 4 of their papers we have counts for
4 papers
Data-Efficient Training of CNNs and Transformers with Coresets: A Stability Perspective
Animesh Gupta, Irtiza Hasan, Dilip K. Prasad +1
Coreset selection is among the most effective ways to reduce the training time of CNNs, however, only limited is known on how the resultant models will behave under variations of t…
Adaptive Fine-Grained Sketch-Based Image Retrieval
Ayan Kumar Bhunia, Aneeshan Sain, Parth Shah +4
The recent focus on Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) has shifted towards generalising a model to new categories without any training data from them. In real-worl…
Syft 0.5: A Platform for Universally Deployable Structured Transparency
Adam James Hall, Madhava Jay, Tudor Cebere +20
We present Syft 0.5, a general-purpose framework that combines a core group of privacy-enhancing technologies that facilitate a universal set of structured transparency systems. Th…
[RE] Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation
Haswanth Aekula, Sugam Garg, Animesh Gupta
Despite widespread use in natural language processing (NLP) tasks, word embeddings have been criticized for inheriting unintended gender bias from training corpora. programmer is m…