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Jing Dong

14 papers hereh-index 13617 citations38 works total

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

author position
  • first author4
  • middle author6
  • last author4

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • math.PR11
  • math.OC3
same name
  • Jing Dong — 31 papers, h 28
  • Jing Dong — 16 papers, h 5
  • Jing Dong — 13 papers, h 6
  • Jing Dong — 9 papers, h 3
  • Jing Dong — 7 papers, h 7
  • Jing Dong — 6 papers, h 15

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
20122021
most citedA Primal-Dual Approach to Constrained Markov Decision Processes

15 citations · 48 across the 14 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

math.PR2020

Existence and Approximations of Moments for Polling Systems under the Binomial-Exhaustive Policy

Yue Hu, Jing Dong, Ohad Perry

We establish sufficient conditions for the existence of moments of the steady-state queue in polling systems operating under the binomial-exhaustive policy (BEP). We assume that th…

math.PR2020

Spectral Gap of Replica Exchange Langevin Diffusion on Mixture Distributions

Jing Dong, Xin T. Tong

Langevin diffusion (LD) is one of the main workhorses for sampling problems. However, its convergence rate can be significantly reduced if the target distribution is a mixture of m…

math.PR2020★ 1 cited

Asymptotic Optimality of the Binomial-Exhaustive Policy for Polling Systems with Large Switchover Times

Yue Hu, Jing Dong, Ohad Perry

We study an optimal-control problem of polling systems with large switchover times, when a holding cost is incurred on the queues. In particular, we consider a stochastic network w…

math.OC2020★ 7 cited

Replica Exchange for Non-Convex Optimization

Jing Dong, Xin T. Tong

Gradient descent (GD) is known to converge quickly for convex objective functions, but it can be trapped at local minima. On the other hand, Langevin dynamics (LD) can explore the…

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