Tanuj Hasija

22 papers Misc 6Journal 11Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Comprehensive Guide to Multiset Canonical Correlation Analysis and Its Application to Joint Blind Source Separation.
IEEE Trans. Signal Process.
Isabell Lehmann, Ben Gabrielson, Tanuj Hasija, Tülay Adali
2026 J jnl
Explainable AI Using Inherently Interpretable Components for Wearable-based Health Monitoring.
CoRR
Maurice Kuschel, Solveig Vieluf, Claus Reinsberger, Tobias Loddenkemper, Tanuj Hasija
2025 Misc conf
Explaining Representations in Correlation-based Deep Multiview Representation Learning.
ICASSP
Maurice Kuschel, Amr Alkhatib, Tanuj Hasija, Henrik Boström
2025 J jnl
Improving wearable-based seizure prediction by feature fusion using an explainable growing network.
Artif. Intell. Medicine
Tanuj Hasija, Maurice Kuschel, Michele Jackson, Stephanie Dailey, Henric Menne, Claus Reinsberger, Solveig Vieluf, Tobias Loddenkemper
2024 J jnl
Identifying the Relationship Structure Among Multiple Datasets Using Independent Vector Analysis: Application to Multi-Task fMRI Data.
IEEE Access
Isabell Lehmann, Tanuj Hasija, Ben Gabrielson, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Tülay Adali
2024 Misc conf
Rademacher Complexity Regularization for Correlation-Based Multiview Representation Learning.
ICASSP
Maurice Kuschel, Tanuj Hasija, Timothy Marrinan
2023 J jnl
Developing a deep canonical correlation-based technique for seizure prediction.
Expert Syst. Appl.
Solveig Vieluf, Tanuj Hasija, Maurice Kuschel, Claus Reinsberger, Tobias Loddenkemper
2023 — conf
Geodesic-Based Relaxation For Deep Canonical Correlation Analysis.
MLSP
Maurice Kuschel, Timothy Marrinan, Tanuj Hasija
2022 — conf
A GLRT for estimating the number of correlated components in sample-poor mCCA.
EUSIPCO
Tanuj Hasija, Timothy Marrinan
2022 Misc conf
Multi-Task fMRI Data Fusion Using IVA and PARAFAC2.
ICASSP
Isabell Lehmann, Evrim Acar, Tanuj Hasija, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Peter J. Schreier, Tülay Adali
2020 J jnl
Determining the dimension and structure of the subspace correlated across multiple data sets.
Signal Process.
Tanuj Hasija, Timothy Marrinan, Christian Lameiro, Peter J. Schreier
2019 J jnl
Determining the Dimension and Structure of the Subspace Correlated Across Multiple Data Sets.
CoRR
Tanuj Hasija, Christian Lameiro, Timothy Marrinan, Peter J. Schreier
2019 Misc conf
Estimating the Number of Correlated Components Based on Random Projections.
ICASSP
Christian Lameiro, Tanuj Hasija, Tim Marrinan, Peter J. Schreier
2019 Misc conf
Source Enumeration and Robust Voice Activity Detection in Wireless Acoustic Sensor Networks.
ACSSC
Tanuj Hasija, Martin Gölz, Michael Muma, Peter J. Schreier, Abdelhak M. Zoubir
2018 — conf
Complete Model Selection in Multiset Canonical Correlation Analysis.
EUSIPCO
Tim Marrinan, Tanuj Hasija, Christian Lameiro, Peter J. Schreier
2017 J jnl
Determining the Dimension of the Improper Signal Subspace in Complex-Valued Data.
CoRR
Tanuj Hasija, Christian Lameiro, Peter J. Schreier
2017 J jnl
Determining the Dimension of the Improper Signal Subspace in Complex-Valued Data.
IEEE Signal Process. Lett.
Tanuj Hasija, Christian Lameiro, Peter J. Schreier
2016 Misc conf
Bootstrap-based detection of the number of signals correlated across multiple data sets.
ACSSC
Tanuj Hasija, Yang Song, Peter J. Schreier, David Ramírez
2016 J jnl
Canonical correlation analysis of high-dimensional data with very small sample support.
CoRR
Yang Song, Peter J. Schreier, David Ramírez, Tanuj Hasija
2016 J jnl
Canonical correlation analysis of high-dimensional data with very small sample support.
Signal Process.
Yang Song, Peter J. Schreier, David Ramírez, Tanuj Hasija
2016 — conf
Detecting the dimension of the subspace correlated across multiple data sets in the sample poor regime.
SSP
Tanuj Hasija, Yang Song, Peter J. Schreier, David Ramírez
2016 — conf
Determining the number of signals correlated across multiple data sets for small sample support.
EUSIPCO
Yang Song, Tanuj Hasija, Peter J. Schreier, David Ramírez