11 citations · 21 across the 4 of their papers we have counts for
4 papers
Modified Kantorovich-type Sampling Series in Orlicz Space Frameworks
Pooja Gupta
This study examines a modified Kantorovich approach applied to generalized sampling series. The paper establishes that the approximation order to a function using these modified op…
Rawlsian Fair Adaptation of Deep Learning Classifiers
Kulin Shah, Pooja Gupta, Amit Deshpande +1
Group-fairness in classification aims for equality of a predictive utility across different sensitive sub-populations, e.g., race or gender. Equality or near-equality constraints i…
DeConFuse : A Deep Convolutional Transform based Unsupervised Fusion Framework
Pooja Gupta, Jyoti Maggu, Angshul Majumdar +2
This work proposes an unsupervised fusion framework based on deep convolutional transform learning. The great learning ability of convolutional filters for data analysis is well ac…
ConFuse: Convolutional Transform Learning Fusion Framework For Multi-Channel Data Analysis
Pooja Gupta, Jyoti Maggu, Angshul Majumdar +2
This work addresses the problem of analyzing multi-channel time series data %. In this paper, we by proposing an unsupervised fusion framework based on %the recently proposed convo…