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A. Wagner

4 papers hereh-index 229 citations4 works total

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

author position
  • first author1
  • middle author1
  • last author2

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

fields
  • cs.LG2
  • eess.SP1
  • stat.AP1
same name
  • A. Wagner — 120 papers, h 32
  • A. Wagner — 40 papers, h 22
  • A. Wagner — 37 papers, h 20
  • A. Wagner — 29 papers, h 39
  • A. Wagner — 24 papers
  • A. Wagner — 24 papers, h 7

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 citedLow-Rank Matrix Recovery from Row-and-Column Affine Measurements

7 citations · 11 across the 4 of their papers we have counts for

collaborators

4 papers

eess.SP2017★ 1 cited

Wrist Sensor Fusion Enables Robust Gait Quantification Across Walking Scenarios

Zeev Waks, Itzik Mazeh, Chen Admati +3

Quantifying step abundance via single wrist-worn accelerometers is a common approach for encouraging active lifestyle and tracking disease status. Nonetheless, step counting accura…

stat.AP2017

A Wavelet-Based Approach To Monitoring Parkinson's Disease Symptoms

Avishai Wagner, Naama Fixler, Yehezkel S. Resheff

Parkinson's disease is a neuro-degenerative disorder affecting tens of millions of people worldwide. Lately, there has been considerable interest in systems for at-home monitoring…

cs.LG2015★ 3 cited

Clustering Noisy Signals with Structured Sparsity Using Time-Frequency Representation

Tom Hope, Avishai Wagner, Or Zuk

We propose a simple and efficient time-series clustering framework particularly suited for low Signal-to-Noise Ratio (SNR), by simultaneous smoothing and dimensionality reduction a…

cs.LG2015★ 7 cited

Low-Rank Matrix Recovery from Row-and-Column Affine Measurements

Avishai Wagner, Or Zuk

We propose and study a row-and-column affine measurement scheme for low-rank matrix recovery. Each measurement is a linear combination of elements in one row or one column of a mat…

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