5 citations · 9 across the 6 of their papers we have counts for
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cs.IR2019
Balancing Accuracy and Diversity in Recommendations using Matrix Completion Framework
Anupriya Gogna, Angshul Majumdar
Design of recommender systems aimed at achieving high prediction accuracy is a widely researched area. However, several studies have suggested the need for diversified recommendati…
cs.CV2019
Discriminative Autoencoder for Feature Extraction: Application to Character Recognition
Anupriya Gogna, Angshul Majumdar
Conventionally, autoencoders are unsupervised representation learning tools. In this work, we propose a novel discriminative autoencoder. Use of supervised discriminative learning…
eess.SP2019
Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals
Anupriya Gogna, Angshul Majumdar, Rabab Ward
In this work we propose an autoencoder based framework for simultaneous reconstruction and classification of biomedical signals. Previously these two tasks, reconstruction and clas…