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Rahul Singh

23 papers hereh-index 191.8k citations73 works total

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

author position
  • sole author1
  • first author13
  • middle author8

Across the 22 of 23 papers where every author was matched, so the position is known.

fields
  • cs.LG10
  • stat.ML4
  • cs.CL3
  • cs.IT2
  • cs.NI2
  • math.OC2
same name
  • Rahul Singh — 6 papers, h 6
  • Rahul Singh — 4 papers, h 14
  • Rahul Singh — 3 papers
  • Rahul Singh — 3 papers
  • Rahul Singh — 3 papers
  • Rahul Singh — 2 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
20172021
most citedScheduling Policies for Minimizing Age of Information in Broadcast Wireless Networks

34 citations · 99 across the 14 of their papers we have counts for

collaborators
Showing stat.MLShow all

4 papers · 1 filter

stat.ML2021

Inference of collective Gaussian hidden Markov models

Rahul Singh, Yongxin Chen

We consider inference problems for a class of continuous state collective hidden Markov models, where the data is recorded in aggregate (collective) form generated by a large popul…

stat.ML2020★ 2 cited

Filtering for Aggregate Hidden Markov Models with Continuous Observations

Qinsheng Zhang, Rahul Singh, Yongxin Chen

We consider a class of filtering problems for large populations where each individual is modeled by the same hidden Markov model (HMM). In this paper, we focus on aggregate inferen…

stat.ML2020

Incremental inference of collective graphical models

Rahul Singh, Isabel Haasler, Qinsheng Zhang +2

We consider incremental inference problems from aggregate data for collective dynamics. In particular, we address the problem of estimating the aggregate marginals of a Markov chai…

stat.ML2017★ 1 cited

Kiefer Wolfowitz Algorithm is Asymptotically Optimal for a Class of Non-Stationary Bandit Problems

Rahul Singh, Taposh Banerjee

We consider the problem of designing an allocation rule or an "online learning algorithm" for a class of bandit problems in which the set of control actions available at each time…

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