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Qiang Huang

Harbin Institute of Technology (Shenzhen)

31 papers hereh-index 14792 citations50 works total

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

author position
  • first author3
  • middle author25

Across the 28 of 31 papers where every author was matched, so the position is known.

fields
  • cs.CL8
  • cs.CV7
  • cs.LG6
  • cs.DB4
  • cs.IR3
  • cs.AI2
affiliations
  • Harbin Institute of Technology (Shenzhen)
Homepage
same name
  • Qiang Huang — 19 papers, h 16
  • Qiang Huang — 5 papers, h 4
  • Qiang Huang — 4 papers, h 4
  • Qiang Huang — 2 papers, h 1
  • Qiang Huang — 2 papers, h 2
  • Qiang Huang — 2 papers, h 8

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
20202026
most citedSAH: Shifting-aware Asymmetric Hashing for Reverse k-Maximum Inner Product Search

4 citations · 16 across the 27 of their papers we have counts for

collaborators
Showing cs.DBShow all

4 papers · 1 filter

cs.DB2023

Lightweight-Yet-Efficient: Revitalizing Ball-Tree for Point-to-Hyperplane Nearest Neighbor Search

Qiang Huang, Anthony K. H. Tung

Finding the nearest neighbor to a hyperplane (or Point-to-Hyperplane Nearest Neighbor Search, simply P2HNNS) is a new and challenging problem with applications in many research dom…

cs.DB2022

DIOT: Detecting Implicit Obstacles from Trajectories

Yifan Lei, Qiang Huang, Mohan Kankanhalli +1

In this paper, we study a new data mining problem of obstacle detection from trajectory data. Intuitively, given two kinds of trajectories, i.e., reference and query trajectories,…

cs.DB2021★ 2 cited

A Generic Distributed Clustering Framework for Massive Data

Pingyi Luo, Qiang Huang, Anthony K. H. Tung

In this paper, we introduce a novel Generic distributEd clustEring frameworK (GEEK) beyond k-means clustering to process massive amounts of data. To deal with different data type…

cs.DB2020★ 3 cited

Locality-Sensitive Hashing Scheme based on Longest Circular Co-Substring

Yifan Lei, Qiang Huang, Mohan Kankanhalli +1

Locality-Sensitive Hashing (LSH) is one of the most popular methods for c-Approximate Nearest Neighbor Search (c-ANNS) in high-dimensional spaces. In this paper, we propose a n…

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