Anupriya Gogna

发表

Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals

Rabab Kreidieh Ward, Angshul Majumdar, Anupriya Gogna, 2017, IEEE Transactions on Biomedical Engineering.

Matrix Recovery Using Split Bregman

Angshul Majumdar, Anupriya Gogna, Ankita Shukla, 2014, 2014 22nd International Conference on Pattern Recognition.

Supervised Learning in Matrix Completion Framework for Recommender System Design

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2016, COMAD.

A Low-Rank Matrix Recovery Approach for Energy Efficient EEG Acquisition for a Wireless Body Area Network

Rabab Kreidieh Ward, Angshul Majumdar, Anupriya Gogna, 2014, Sensors.

DiABlO: Optimization based design for improving diversity in recommender system

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2017, Inf. Sci..

Comparative analysis of evolutionary algorithms for image enhancement pdf

Anupriya Gogna, Akash Tayal, A. Tayal, 2012, Int. J. Metaheuristics.

Deep Dictionary Learning vs Deep Belief Network vs Stacked Autoencoder: An Empirical Analysis

Angshul Majumdar, Anupriya Gogna, Vanika Singhal, 2016, ICONIP.

Design of signal-matched critically sampled FIR rational filterbank

Anupriya Gogna, Anubha Gupta, Gade Narayana Sri Harsha, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Blind compressive sensing formulation incorporating metadata for recommender system design

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2015, APSIPA Transactions on Signal and Information Processing.

Matrix factorization model using Kacmarz algorithm: Application in sensor localization

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2015, 2015 IEEE International Conference on Digital Signal Processing (DSP).

Fast Acquisition for Quantitative MRI Maps: Sparse Recovery from Non-Linear Measurements

Angshul Majumdar, Anupriya Gogna, 2016, 2016 Data Compression Conference (DCC).

Kernel L1-Minimization: Application to Kernel Sparse Representation Based Classification

Angshul Majumdar, Anupriya Gogna, 2016, ICONIP.

Semi Supervised Autoencoder

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2016, ICONIP.

Discriminative Autoencoder for Feature Extraction: Application to Character Recognition

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2018, Neural Processing Letters.

Nuclear Norm Regularized Randomized Neural Network

Angshul Majumdar, Anupriya Gogna, 2016, ICONIP.

Metaheuristics: review and application

Anupriya Gogna, Akash Tayal, A. Tayal, 2013, J. Exp. Theor. Artif. Intell..

Blind Compressive Sensing Framework for Collaborative Filtering pdf

Angshul Majumdar, Anupriya Gogna, 2015, ArXiv.

Distributed Elastic Net Regularized Blind Compressive Sensing for Recommender System Design

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2014, COMAD.

A Comprehensive Recommender System Model: Improving Accuracy for Both Warm and Cold Start Users

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2015, IEEE Access.

Matrix completion incorporating auxiliary information for recommender system design

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2015, Expert Syst. Appl..

Balancing accuracy and diversity in recommendations using matrix completion framework pdf

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2017, Knowl. Based Syst..

Split Bregman algorithms for sparse / joint-sparse and low-rank signal recovery: Application in compressive hyperspectral imaging

Angshul Majumdar, Hemant Kumar Aggarwal, Anupriya Gogna, 2014, 2014 IEEE International Conference on Image Processing (ICIP).

SVD free matrix completion with online bias correction for Recommender systems

Angshul Majumdar, Anupriya Gogna, A. Majumdar, 2015, 2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR).

Stacked Robust Autoencoder for Classification

Angshul Majumdar, Anupriya Gogna, Kavya Gupta, 2016, ICONIP.