258 citations · 511 across the 17 of their papers we have counts for
6 papers · 2 filters
Alpha Elimination: Using Deep Reinforcement Learning to Reduce Fill-In during Sparse Matrix Decomposition
Arpan Dasgupta, Pawan Kumar
A large number of computational and scientific methods commonly require decomposing a sparse matrix into triangular factors as LU decomposition. A common problem faced during this…
Reinforcement Learning Based Sensor Optimization for Bio-markers
Sajal Khandelwal, Pawan Kumar, Syed Azeemuddin
Radio frequency (RF) biosensors, in particular those based on inter-digitated capacitors (IDCs), are pivotal in areas like biomedical diagnosis, remote sensing, and wireless commun…
Light-weight Deep Extreme Multilabel Classification
Istasis Mishra, Arpan Dasgupta, Pratik Jawanpuria +2
Extreme multi-label (XML) classification refers to the task of supervised multi-label learning that involves a large number of labels. Hence, scalability of the classifier with inc…
Angle based dynamic learning rate for gradient descent
Neel Mishra, Pawan Kumar
In our work, we propose a novel yet simple approach to obtain an adaptive learning rate for gradient-based descent methods on classification tasks. Instead of the traditional appro…
Qualitative Data Augmentation for Performance Prediction in VLSI circuits
Prasha Srivastava, Pawan Kumar, Zia Abbas
Various studies have shown the advantages of using Machine Learning (ML) techniques for analog and digital IC design automation and optimization. Data scarcity is still an issue fo…
Review of Extreme Multilabel Classification
Arpan Dasgupta, Preeti Lamba, Ankita Kushwaha +4
Extreme multi-label classification or XMLC, is an active area of interest in machine learning. Compared to traditional multi-label classification, here the number of labels is extr…