In this note, we demonstrate a first-of-its-kind provable convergence of...
Deep Operator Networks are an increasingly popular paradigm for solving
...
In this note we demonstrate provable convergence of SGD to the global mi...
In recent times machine learning methods have made significant advances ...
A particular direction of recent advance about stochastic deep-learning
...
A fundamental quest in the theory of deep-learning is to understand the
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"Deep Learning"/"Deep Neural Nets" is a technological marvel that is now...
In this work we demonstrate provable guarantees on the training of depth...
In recent times many state-of-the-art machine learning models have been ...
RMSProp and ADAM continue to be extremely popular algorithms for trainin...
Motivated by the resurgence of neural networks in being able to solve co...
In "Dictionary Learning" one tries to recover incoherent matrices A^* ∈R...
In this paper we investigate the family of functions representable by de...