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Electronic Colloquium on Computational Complexity

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REPORTS > AUTHORS > AMITABH BASU :
All reports by Author Amitabh Basu :

TR17-190 | 6th November 2017
Anirbit Mukherjee, Amitabh Basu

Lower bounds over Boolean inputs for deep neural networks with ReLU gates.

Motivated by the resurgence of neural networks in being able to solve complex learning tasks we undertake a study of high depth networks using ReLU gates which implement the function $x \mapsto \max\{0,x\}$. We try to understand the role of depth in such neural networks by showing size lowerbounds against ... more >>>


TR17-098 | 28th May 2017
Raman Arora, Amitabh Basu , Poorya Mianjy, Anirbit Mukherjee

Understanding Deep Neural Networks with Rectified Linear Units

Revisions: 2

In this paper we investigate the family of functions representable by deep neural networks (DNN) with rectified linear units (ReLU). We give the first-ever polynomial time (in the size of data) algorithm to train to global optimality a ReLU DNN with one hidden layer, assuming the input dimension and number ... more >>>




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