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Miao Zhang

4 papers here

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

author position
  • first author4

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

fields
  • cs.LG4
same name
  • Miao Zhang — 7 papers, h 14
  • Miao Zhang — 5 papers
  • Miao Zhang — 4 papers, h 2
  • Miao Zhang — 3 papers, h 6
  • Miao Zhang — 2 papers
  • Miao Zhang — 2 papers, h 6

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 citediDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients

16 citations · 36 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2021★ 16 cited

iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients

Miao Zhang, Steven Su, Shirui Pan +3

\textit{Differentiable ARchiTecture Search} (DARTS) has recently become the mainstream of neural architecture search (NAS) due to its efficiency and simplicity. With a gradient-bas…

cs.LG2019★ 1 cited

Efficient Novelty-Driven Neural Architecture Search

Miao Zhang, Huiqi Li, Shirui Pan +2

One-Shot Neural architecture search (NAS) attracts broad attention recently due to its capacity to reduce the computational hours through weight sharing. However, extensive experim…

cs.LG2019★ 7 cited

High Dimensional Bayesian Optimization via Supervised Dimension Reduction

Miao Zhang, Huiqi Li, Steven Su

Bayesian optimization (BO) has been broadly applied to computational expensive problems, but it is still challenging to extend BO to high dimensions. Existing works are usually und…

cs.LG2019★ 12 cited

Multi-level CNN for lung nodule classification with Gaussian Process assisted hyperparameter optimization

Miao Zhang, Huiqi Li, Juan Lyu +2

This paper investigates lung nodule classification by using deep neural networks (DNNs). Hyperparameter optimization in DNNs is a computationally expensive problem, where evaluatin…

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