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researcher

H. Lam

79 papers hereh-index 232.9k citations159 works total

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

author position
  • sole author5
  • first author20
  • middle author38
  • last author15

Across the 78 of 79 papers where every author was matched, so the position is known.

fields
  • stat.ME22
  • math.OC14
  • cs.LG13
  • math.PR8
  • eess.SY5
  • stat.ML5
same name
  • H. Lam — 25 papers, h 19
  • H. Lam — 8 papers, h 29
  • H. Lam — 7 papers, h 5
  • H. Lam — 6 papers, h 1
  • H. Lam — 6 papers, h 4
  • H. Lam — 6 papers

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
20112026
most citedAccelerated Evaluation of Automated Vehicles Safety in Lane Change Scenarios Based on Importance Sampling Techniques

457 citations · 696 across the 72 of their papers we have counts for

collaborators
Showing 2012 · math.PRShow all

4 papers · 2 filters

math.PR2012

Two-parameter Sample Path Large Deviations for Infinite Server Queues

J. Blanchet, X. Chen, H. Lam

Let Qλ​(t,y) be the number of people present at time t with y units of remaining service time in an infinite server system with arrival rate equal to λ>0. In the presence…

math.PR2012

Chernoff-Hoeffding Bounds for Markov Chains: Generalized and Simplified

Kai-Min Chung, Henry Lam, Zhenming Liu +1

We prove the first Chernoff-Hoeffding bounds for general nonreversible finite-state Markov chains based on the standard L_1 (variation distance) mixing-time of the chain. Specifica…

math.PR2012★ 2 cited

Rare-Event Simulation for Many-Server Queues

Jose Blanchet, Henry Lam

We develop rare-event simulation methodology for the analysis of loss events in a many-server loss system under quality-driven regime, focusing on the steady-state loss probability…

math.PR2012

Efficient Rare-event Simulation for Perpetuities

Jose Blanchet, Henry Lam, Bert Zwart

We consider perpetuities of the form D = B_1 exp(Y_1) + B_2 exp(Y_1+Y_2) + ... where the Y_j's and B_j's might be i.i.d. or jointly driven by a suitable Markov chain. We assume tha…

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