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IEEE Transactions on Neural Networks and Learning Systems
|
January 24, 2017
Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices
Anoop Cherian, Suvrit Sra
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|
August 15, 2014
Efficient nearest neighbors via robust sparse hashing
Anoop Cherian, Suvrit Sra, Vassilios Morellas, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
July 23, 2013
Jensen-Bregman LogDet divergence with application to efficient similarity search for covariance matrices
Anoop Cherian, Suvrit Sra, Arindam Banerjee, et al.
Advances in Neural Information Processing Systems
|
May 13, 2022
Can contrastive learning avoid shortcut solutions?
Joshua Robinson, Li Sun, Ke Yu, et al.
Frontiers in Artificial Intelligence
|
March 18, 2021
An Interpretable Predictive Model of Vaccine Utilization for Tanzania
Ramkumar Hariharan, Johnna Sundberg, Giacomo Gallino, et al.
Page
of 1
Search research articles
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Showing results (1-10 of 5) with videos related to
Sort By:
Page
of 1
IEEE Transactions on Neural Networks and Learning Systems
|
January 24, 2017
Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices
Anoop Cherian, Suvrit Sra
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|
August 15, 2014
Efficient nearest neighbors via robust sparse hashing
Anoop Cherian, Suvrit Sra, Vassilios Morellas, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
July 23, 2013
Jensen-Bregman LogDet divergence with application to efficient similarity search for covariance matrices
Anoop Cherian, Suvrit Sra, Arindam Banerjee, et al.
Advances in Neural Information Processing Systems
|
May 13, 2022
Can contrastive learning avoid shortcut solutions?
Joshua Robinson, Li Sun, Ke Yu, et al.
Frontiers in Artificial Intelligence
|
March 18, 2021
An Interpretable Predictive Model of Vaccine Utilization for Tanzania
Ramkumar Hariharan, Johnna Sundberg, Giacomo Gallino, et al.
Page
of 1