Lp Quasi-norm Minimization: Algorithm and Applications.

Omar M Sleem, M E Ashour, N S Aybat, Constantino M Lagoa

Abstract readPreprint

In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Omar M SleemDepartment of Electrical Engineering, Pennsylvania State University, State College, PA, 16802 USA.ORCID 0000-0002-4994-0808

M E AshourWireless R&D Department, Qualcomm Technologies, Inc, San Diego, CA, 92121, USA.

N S AybatDepartment of Industrial and Manufacturing Engineering, Pennsylvania State University, State College, PA, 16802 USA.

Constantino M LagoaDepartment of Electrical Engineering, Pennsylvania State University, State College, PA, 16802 USA.

Funding

Phase 1 clinical trial to develop a personalized adaptive text message intervention using control systems engineering tools to increase physical activity in early adulthoodR01HL142732 · NHLBI · PENNSYLVANIA STATE UNIVERSITY, THE · PI CONROY, DAVID E., LAGOA, CONSTANTINO MANUEL · 2018 to 2021

$2.4M

NHLBI NIH HHS R01 HL142732

6 · The paper itself

Abstract

Sparsity finds applications in diverse areas such as statistics, machine learning, and signal processing. Computations over sparse structures are less complex compared to their dense counterparts and need less storage. This paper proposes a heuristic method for retrieving sparse approximate solutions of optimization problems via minimizing the

Indexed as

ADMMCompressed sensingMatrix completionProximal gradient methodRank minimizationSparsitySystem identification

Identifiers

PMID38076799

DOI10.21203/rs.3.rs-3632062/v1

PMCPMC10705602

What OpenQuestion holds

Textmetadata

LicenceCC BY

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.