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Ding Ding

26 papers hereh-index 5223 citations6 works total

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

author position
  • middle author1

Across the 1 of 26 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.HC3
  • cs.IR3
  • cs.LG3
  • cs.CR2
  • cs.CV2
same name
  • Ding Ding — 4 papers
  • Ding Ding — 2 papers
  • Ding Ding — 2 papers
  • Ding Ding — 1 paper
  • Ding Ding — 1 paper, h 7
  • Ding Ding — 1 paper

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
20192022
most citedFirst Infrastructure and Experimentation in Echo-debugging

1 citations · 1 across the 14 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.HC2022

Revisiting Piggyback Prototyping: Examining Benefits and Tradeoffs in Extending Existing Social Computing Systems

Daniel A. Epstein, Fannie Liu, Andrés Monroy-Hernández +1

The CSCW community has a history of designing, implementing, and evaluating novel social interactions in technology, but the process requires significant technical effort for uncer…

cs.NE2022

Explanation-Guided Fairness Testing through Genetic Algorithm

Ming Fan, Wenying Wei, Wuxia Jin +2

The fairness characteristic is a critical attribute of trusted AI systems. A plethora of research has proposed diverse methods for individual fairness testing. However, they are su…

cs.LG2022

BigDL 2.0: Seamless Scaling of AI Pipelines from Laptops to Distributed Cluster

Jason Dai, Ding Ding, Dongjie Shi +13

Most AI projects start with a Python notebook running on a single laptop; however, one usually needs to go through a mountain of pains to scale it to handle larger dataset (for bot…

cs.SI2022

MiDaS: Representative Sampling from Real-world Hypergraphs

Minyoung Choe, Jaemin Yoo, Geon Lee +3

Graphs are widely used for representing pairwise interactions in complex systems. Since such real-world graphs are large and often evergrowing, sampling a small representative subg…

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