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researcher

Liwei Wang

65 papers hereh-index 5115.1k citations125 works total

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

author position
  • first author1
  • middle author31
  • last author31

Across the 63 of 65 papers where every author was matched, so the position is known.

fields
  • cs.LG36
  • cs.CV17
  • cs.CL7
  • cs.GT2
  • cs.CC1
  • cs.DB1
same name
  • Liwei Wang — 44 papers, h 34
  • Liwei Wang — 23 papers, h 22
  • Liwei Wang — 15 papers, h 18
  • Liwei Wang — 12 papers, h 26
  • Liwei Wang — 9 papers, h 5
  • Liwei Wang — 8 papers, h 9

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
20132021
most citedDual Learning for Machine Translation

597 citations · 2.9k across the 64 of their papers we have counts for

collaborators
Showing 2014Show all

4 papers · 1 filter

cs.GT2014★ 20 cited

A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search

Di He, Wei Chen, Liwei Wang +1

Sponsored search is an important monetization channel for search engines, in which an auction mechanism is used to select the ads shown to users and determine the prices charged fr…

cs.GT2014★ 1 cited

Generalized Second Price Auction with Probabilistic Broad Match

Wei Chen, Di He, Tie-Yan Liu +3

Generalized Second Price (GSP) auctions are widely used by search engines today to sell their ad slots. Most search engines have supported broad match between queries and bid keywo…

cs.CV2014★ 116 cited

Can Image-Level Labels Replace Pixel-Level Labels for Image Parsing

Zhiwu Lu, Zhenyong Fu, Tao Xiang +2

This paper presents a weakly supervised sparse learning approach to the problem of noisily tagged image parsing, or segmenting all the objects within a noisily tagged image and ide…

cs.DB2014

Differentially Private Data Releasing for Smooth Queries with Synthetic Database Output

Chi Jin, Ziteng Wang, Junliang Huang +2

We consider accurately answering smooth queries while preserving differential privacy. A query is said to be K-smooth if it is specified by a function defined on [−1,1]d whose…

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