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Xiaopeng Li

4 papers hereh-index 9670 citations17 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG4
same name
  • Xiaopeng Li — 16 papers
  • Xiaopeng Li — 14 papers, h 9
  • Xiaopeng Li — 10 papers, h 19
  • Xiaopeng Li — 8 papers, h 5
  • Xiaopeng Li — 6 papers, h 10
  • Xiaopeng Li — 5 papers, h 8

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedNot All Attention Is Needed: Gated Attention Network for Sequence Data

2 citations · 2 across the 1 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2019★ 2 cited

Not All Attention Is Needed: Gated Attention Network for Sequence Data

Lanqing Xue, Xiaopeng Li, Nevin L. Zhang

Although deep neural networks generally have fixed network structures, the concept of dynamic mechanism has drawn more and more attention in recent years. Attention mechanisms comp…

cs.LG2018

Learning Sparse Deep Feedforward Networks via Tree Skeleton Expansion

Zhourong Chen, Xiaopeng Li, Nevin L. Zhang

Despite the popularity of deep learning, structure learning for deep models remains a relatively under-explored area. In contrast, structure learning has been studied extensively f…

cs.LG2018

Building Sparse Deep Feedforward Networks using Tree Receptive Fields

Xiaopeng Li, Zhourong Chen, Nevin L. Zhang

Sparse connectivity is an important factor behind the success of convolutional neural networks and recurrent neural networks. In this paper, we consider the problem of learning spa…

cs.LG2018

Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering

Xiaopeng Li, Zhourong Chen, Leonard K. M. Poon +1

We investigate a variant of variational autoencoders where there is a superstructure of discrete latent variables on top of the latent features. In general, our superstructure is a…

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