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researcher

S. Kay

4 papers hereh-index 5135.3k citations245 works total

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

author position
  • middle author2
  • last author2

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

fields
  • stat.ML2
  • eess.SY1
  • physics.data-an1
same name
  • S. Kay — 66 papers, h 39
  • S. Kay — 43 papers, h 15
  • S. Kay — 15 papers, h 3
  • S. Kay — 8 papers, h 1
  • S. Kay — 1 paper, h 67
  • S. Kay — 1 paper, h 3

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 citedAdaptive Signal Detection and Parameter Estimation in Unknown Colored Gaussian Noise

3 citations · 3 across the 1 of their papers we have counts for

collaborators

4 papers

stat.ML2017

On Bayesian Exponentially Embedded Family for Model Order Selection

Zhenghan Zhu, Steven Kay

In this paper, we derive a Bayesian model order selection rule by using the exponentially embedded family method, termed Bayesian EEF. Unlike many other Bayesian model selection me…

physics.data-an2016★ 3 cited

Adaptive Signal Detection and Parameter Estimation in Unknown Colored Gaussian Noise

Bo Tang, Haibo He, Steven Kay

This paper considers the general signal detection and parameter estimation problem in the presence of colored Gaussian noise disturbance. By modeling the disturbance with an autore…

eess.SY2016

Detection of False Data Injection Attacks in Smart Grid under Colored Gaussian Noise

Bo Tang, Jun Yan, Steven Kay +1

In this paper, we consider the problems of state estimation and false data injection detection in smart grid when the measurements are corrupted by colored Gaussian noise. By model…

stat.ML2016

EEF: Exponentially Embedded Families with Class-Specific Features for Classification

Bo Tang, Steven Kay, Haibo He +1

In this letter, we present a novel exponentially embedded families (EEF) based classification method, in which the probability density function (PDF) on raw data is estimated from…

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