252 citations · 435 across the 19 of their papers we have counts for
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Smoothed Analysis of Tensor Decompositions
Aditya Bhaskara, Moses Charikar, Ankur Moitra +1
Low rank tensor decompositions are a powerful tool for learning generative models, and uniqueness results give them a significant advantage over matrix decomposition methods. Howev…
Provable Bounds for Learning Some Deep Representations
Sanjeev Arora, Aditya Bhaskara, Rong Ge +1
We give algorithms with provable guarantees that learn a class of deep nets in the generative model view popularized by Hinton and others. Our generative model is an node multi…
Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability
Aditya Bhaskara, Moses Charikar, Aravindan Vijayaraghavan
We give a robust version of the celebrated result of Kruskal on the uniqueness of tensor decompositions: we prove that given a tensor whose decomposition satisfies a robust form of…