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Random Matrix and Information Bottleneck Theory
Understanding spectral properties of deep neural networks using RTM
Study of impact of initialisation and activation functions on signal propagation in deep networks
Study of information flow in deep networks
Optimization on Orthogonal Group
Generalization error analysis with orthogonality constraints
Efficient training of deep neural networks on Riemannian and Stiefel manifold
Compressed Neural Networks
Reducing footprint of deep networks using low-rank and sparse structures
Analysing robustness to adversarial attacks
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