activity
20172019
most citedHow deep learning works --The geometry of deep learning

10 citations · 29 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CR20194 cited

A Restrained Paillier Cryptosystem and Its Applications for Access Control of Common Secret

Xiaojuan Dong, Weiming Zhang, Mohsin Shah +2

The modified Paillier cryptosystem has become extremely popular and applied in many fields, owning to its additive homomorphism. This cryptosystem provides weak private keys and a…

cs.LG20191 cited

Gauge theory and twins paradox of disentangled representations

X. Dong, L. Zhou

Achieving disentangled representations of information is one of the key goals of deep network based machine learning system. Recently there are more discussions on this issue. In t…

cs.LG20193 cited

Understanding over-parameterized deep networks by geometrization

Xiao Dong, Ling Zhou

A complete understanding of the widely used over-parameterized deep networks is a key step for AI. In this work we try to give a geometric picture of over-parameterized deep networ…

cs.LG20197 cited

Geometrization of deep networks for the interpretability of deep learning systems

Xiao Dong, Ling Zhou

How to understand deep learning systems remains an open problem. In this paper we propose that the answer may lie in the geometrization of deep networks. Geometrization is a bridge…

quant-ph2018

Time from quantum state complexity and the pace of time flow

X. Dong, L. Zhou

Based on the hypothesis that the thermodynamic arrow of time is an emergent phenomenon of quantum state complexity evolution, we further propose that the natural pace of time flow…

cs.LG20174 cited

Demystifying AlphaGo Zero as AlphaGo GAN

Xiao Dong, Jiasong Wu, Ling Zhou

The astonishing success of AlphaGo Zero\cite{Silver_AlphaGo} invokes a worldwide discussion of the future of our human society with a mixed mood of hope, anxiousness, excitement an…