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Wenda Zhou

Columbia University

10 papers hereh-index 14845 citations25 works total

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

author position
  • first author3
  • middle author7

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • stat.ML4
  • cs.LG3
  • cs.IT2
  • astro-ph.IM1
affiliations
  • Columbia University
Homepage
same name
  • Wenda Zhou — 3 papers, h 5
  • Wenda Zhou — 3 papers, h 4
  • Wenda Zhou — 2 papers
  • Wenda Zhou — 1 paper, h 12
  • Wenda Zhou — 1 paper, h 2

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
20182022
most citedNon-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach

88 citations · 139 across the 10 of their papers we have counts for

collaborators
Showing 2018 · stat.MLShow all

3 papers · 2 filters

stat.ML2018★ 13 cited

Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions

Shuaiwen Wang, Wenda Zhou, Haihao Lu +2

Consider the following class of learning schemes: $$\hat{\boldsymbolβ} := \arg\min_{\boldsymbolβ}\;\sum_{j=1}^n \ell(\boldsymbol{x}_j^\top\boldsymbolβ; y_j) + λR(\boldsymbolβ),\qqu…

stat.ML2018★ 3 cited

Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data

Victor Veitch, Morgane Austern, Wenda Zhou +2

Empirical risk minimization is the main tool for prediction problems, but its extension to relational data remains unsolved. We solve this problem using recent ideas from graph sam…

stat.ML2018★ 88 cited

Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach

Wenda Zhou, Victor Veitch, Morgane Austern +2

Modern neural networks are highly overparameterized, with capacity to substantially overfit to training data. Nevertheless, these networks often generalize well in practice. It has…

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