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Researcher Evidence Record

Yingqiu Zhu

This bounded record lists 10 Pith paper rows and 0 imported work rows attributed to this corpus identity. The enumerated, non-disputed paper rows include stat.ME, cs.LG, cs.SI work dated 2020 to 2025. The record describes sources and coverage; it makes no judgment about the person.

Compiled coverage vector

Measured lane counts only. Not a trust score or person verdict.

Identity 2 canonical identity row plus typed public identifiers Pith papers 10 attributed paper rows in the Pith corpus, itemized below Imported works 0 imported works beyond the paper ledger Current reviews 0 of 10 papers carrying a current Pith review; presence, not outcome Sourced citations 1 of 10 works with a source-named citation count Coauthors 28 distinct coauthors across shared paper rows
Enumerated paper scope: 5 fields (stat.ME, cs.LG, cs.SI, +2 more) · 2020-2025 sources: authors, author_identifiers · paper_authors · author_works · current_verdicts · cited_works

A sourced case file for attributed work. It is neither a profile score nor a verdict about this researcher.

Attributed works

A bounded ledger from the Pith paper and imported-work queries. Counts and source confidence stay with each work.

  1. 2025 Pith paper

    Density Prediction of Income Distribution Based on Mixed Frequency Data

    stat.ME provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yingqiu Zhu
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  2. 2024 Pith paper

    A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques

    stat.ME provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yingqiu Zhu
    Author position
    13
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  3. 2023 Pith paper

    CluBear: A Subsampling Package for Interactive Statistical Analysis with Massive Data on A Single Machine

    stat.ME provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yingqiu Zhu
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  4. 2023 Pith paper

    Mini-batch Gradient Descent with Buffer

    stat.CO provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yingqiu Zhu
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  5. 2023 Pith paper

    Improved Naive Bayes with Mislabeled Data

    cs.LG provisional measured, no current review

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yingqiu Zhu
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts
  6. 2022 Pith paper

    A Wasserstein distance-based spectral clustering method for transaction data analysis

    stat.ME provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yingqiu Zhu
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  7. 2021 Pith paper

    Subsampling Spectral Clustering for Large-Scale Social Networks

    cs.SI provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yingqiu Zhu
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  8. 2021 Pith paper

    A Sequential Addressing Subsampling Method for Massive Data Analysis under Memory Constraint

    stat.ME provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yingqiu Zhu
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  9. 2020 Pith paper

    Automatic, Dynamic, and Nearly Optimal Learning Rate Specification by Local Quadratic Approximation

    stat.ML provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yingqiu Zhu
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  10. 2020 Pith paper

    Efficient Estimation for Generalized Linear Models on a Distributed System with Nonrandomly Distributed Data

    stat.ME provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yingqiu Zhu
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.

Evidence apparatus

The machinery behind this record. Every lane states whether Pith measured it, did not query it, could not reach it, or withheld it.

LaneStateObservedBoundary and source
identity Measured 2 Canonical identity row plus public typed identifiers.
source=authors, author_identifiers
papers Measured 10 of 10 bounded rows Rows attributed to this author UUID in the Pith corpus.
source=paper_authors
works Measured zero 0 of 0 bounded rows Imported works not duplicated by the paper ledger.
source=author_works
reviews Measured zero 0 of 10 bounded rows Coverage count only. No review outcome is projected onto the person.
source=current_verdicts
citations Measured 1 of 10 bounded rows Counts remain itemized by work and source.
source=cited_works
coauthors Measured 28 of 10 bounded rows Shared-work edges from admitted paper rows.
source=paper_authors
account Unavailable No public count of 1 bounded rows Account metadata is separate from corpus evidence.
source=users.author_id
Public identity sources
  • name variant
    Yingqiu Zhu     backfill
    confidence 0.6

identity history

Enumerated research scope

Fields and dates come only from enumerated, non-disputed Pith paper rows. They do not claim career completeness.

  • stat.ME6 rows
  • cs.LG1 rows
  • cs.SI1 rows
  • stat.CO1 rows
  • stat.ML1 rows
  • 20202 rows
  • 20212 rows
  • 20221 rows
  • 20233 rows
  • 20241 rows
  • 20251 rows
Shared-work index
Record scope

The work queries are bounded. Missing rows may mean measured zero, an unavailable source, a query that did not run, or private data that Pith withheld. The lane table keeps those cases separate.

Paper findings remain attached to papers. They do not become findings about this researcher.