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researcher

D. Ho

16 papers hereh-index 9726.9k citations360 works total

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

author position
  • middle author9
  • last author6

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • math.OC7
  • eess.SY6
  • cs.LG2
  • cs.NI1
same name
  • D. Ho — 20 papers, h 21
  • D. Ho — 19 papers, h 13
  • D. Ho — 6 papers, h 6
  • D. Ho — 4 papers
  • D. Ho — 3 papers, h 18
  • D. Ho — 2 papers, h 22

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

activity
20102022
most citedA New Approach to Linear/Nonlinear Distributed Fusion Estimation Problem

76 citations · 119 across the 16 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

math.OC2019

Distributed Stochastic Block Coordinate Descent for Time-Varying Multi-Agent Optimization

Zhan Yu, Daniel W. C. Ho

In this paper, a class of large-scale distributed nonsmooth convex optimization problem over time-varying multi-agent network is investigated. Specifically, the decision space whic…

eess.SY2019★ 4 cited

A New Approach to Pinning Control of Boolean Networks

Jie Zhong, Daniel W. C. Ho, Jianquan Lu

Boolean networks (BNs) are discrete-time systems where nodes are inter-connected (here we call such connection rule among nodes as network structure), and the dynamics of each gene…

math.OC2019★ 3 cited

Zeroth-Order Stochastic Block Coordinate Type Methods for Nonconvex Optimization

Zhan Yu, Daniel W. C. Ho

We study (constrained) nonconvex (composite) optimization problems where the decision variables vector can be split into blocks of variables. Random block projection is a popular t…

math.OC2019★ 9 cited

Distributed Randomized Gradient-Free Mirror Descent Algorithm for Constrained Optimization

Zhan Yu, Daniel W. C. Ho, Deming Yuan

This paper is concerned with multi-agent optimization problem. A distributed randomized gradient-free mirror descent (DRGFMD) method is developed by introducing a randomized gradie…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.