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researcher

Ke Deng

4 papers hereh-index 111k citations26 works total

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

author position
  • middle author3
  • last author1

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

fields
  • stat.ME2
  • stat.ML2
same name
  • Ke Deng — 20 papers, h 39
  • Ke Deng — 9 papers, h 4
  • Ke Deng — 6 papers, h 1
  • Ke Deng — 5 papers, h 4
  • Ke Deng — 4 papers, h 17
  • Ke Deng — 4 papers, h 3

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
20172021
most citedStratification and Optimal Resampling for Sequential Monte Carlo

4 citations · 8 across the 4 of their papers we have counts for

collaborators

4 papers

stat.ME2021

Partition-Mallows Model and Its Inference for Rank Aggregation

Wanchuang Zhu, Yingkai Jiang, Jun S. Liu +1

Learning how to aggregate ranking lists has been an active research area for many years and its advances have played a vital role in many applications ranging from bioinformatics t…

stat.ML2020★ 2 cited

Multi-level Training and Bayesian Optimization for Economical Hyperparameter Optimization

Yang Yang, Ke Deng, Michael Zhu

Hyperparameters play a critical role in the performances of many machine learning methods. Determining their best settings or Hyperparameter Optimization (HPO) faces difficulties p…

stat.ME2020★ 4 cited

Stratification and Optimal Resampling for Sequential Monte Carlo

Yichao Li, Wenshuo Wang, Ke Deng +1

Sequential Monte Carlo (SMC), also known as particle filters, has been widely accepted as a powerful computational tool for making inference with dynamical systems. A key step in S…

stat.ML2017★ 2 cited

DIMM-SC: A Dirichlet mixture model for clustering droplet-based single cell transcriptomic data

Zhe Sun, Ting Wang, Ke Deng +5

Motivation: Single cell transcriptome sequencing (scRNA-Seq) has become a revolutionary tool to study cellular and molecular processes at single cell resolution. Among existing tec…

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