28 citations · 33 across the 9 of their papers we have counts for
9 papers
Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning
Richa Upadhyay, Ronald Phlypo, Rajkumar Saini +1
This paper presents meta-sparsity, a framework for learning model sparsity, basically learning the parameter that controls the degree of sparsity, that allows deep neural networks…
Giving each task what it needs -- leveraging structured sparsity for tailored multi-task learning
Richa Upadhyay, Ronald Phlypo, Rajkumar Saini +1
In the Multi-task Learning (MTL) framework, every task demands distinct feature representations, ranging from low-level to high-level attributes. It is vital to address the specifi…
Less is More -- Towards parsimonious multi-task models using structured sparsity
Richa Upadhyay, Ronald Phlypo, Rajkumar Saini +1
Model sparsification in deep learning promotes simpler, more interpretable models with fewer parameters. This not only reduces the model's memory footprint and computational needs…
Functional Knowledge Transfer with Self-supervised Representation Learning
Prakash Chandra Chhipa, Muskaan Chopra, Gopal Mengi +7
This work investigates the unexplored usability of self-supervised representation learning in the direction of functional knowledge transfer. In this work, functional knowledge tra…
Depth Contrast: Self-Supervised Pretraining on 3DPM Images for Mining Material Classification
Prakash Chandra Chhipa, Richa Upadhyay, Rajkumar Saini +4
This work presents a novel self-supervised representation learning method to learn efficient representations without labels on images from a 3DPM sensor (3-Dimensional Particle Mea…
Multi-Task Meta Learning: learn how to adapt to unseen tasks
Richa Upadhyay, Prakash Chandra Chhipa, Ronald Phlypo +2
This work proposes Multi-task Meta Learning (MTML), integrating two learning paradigms Multi-Task Learning (MTL) and meta learning, to bring together the best of both worlds. In pa…
Deep Neural Network approaches for Analysing Videos of Music Performances
Foteini Simistira Liwicki, Richa Upadhyay, Prakash Chandra Chhipa +4
This paper presents a framework to automate the labelling process for gestures in musical performance videos with a 3D Convolutional Neural Network (CNN). While this idea was propo…
Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images
Prakash Chandra Chhipa, Richa Upadhyay, Gustav Grund Pihlgren +3
This work presents a novel self-supervised pre-training method to learn efficient representations without labels on histopathology medical images utilizing magnification factors. O…
Sharing to learn and learning to share; Fitting together Meta-Learning, Multi-Task Learning, and Transfer Learning: A meta review
Richa Upadhyay, Ronald Phlypo, Rajkumar Saini +1
Integrating knowledge across different domains is an essential feature of human learning. Learning paradigms such as transfer learning, meta-learning, and multi-task learning refle…