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Q. Ji

14 papers hereh-index 7019.6k citations399 works total

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

author position
  • first author1
  • last author12

Across the 13 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • cs.LG4
  • cs.MM1
same name
  • Q. Ji — 519 papers, h 58
  • Q. Ji — 227 papers, h 3
  • Q. Ji — 174 papers, h 9
  • Q. Ji — 59 papers, h 19
  • Q. Ji — 33 papers, h 2
  • Q. Ji — 10 papers, h 15

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
20152021
most citedAffective Computing for Large-Scale Heterogeneous Multimedia Data: A Survey

79 citations · 161 across the 12 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2021★ 3 cited

DAGs with No Curl: An Efficient DAG Structure Learning Approach

Yue Yu, Tian Gao, Naiyu Yin +1

Recently directed acyclic graph (DAG) structure learning is formulated as a constrained continuous optimization problem with continuous acyclicity constraints and was solved iterat…

cs.LG2020

Type-augmented Relation Prediction in Knowledge Graphs

Zijun Cui, Pavan Kapanipathi, Kartik Talamadupula +2

Knowledge graphs (KGs) are of great importance to many real world applications, but they generally suffer from incomplete information in the form of missing relations between entit…

cs.LG2017★ 2 cited

Deep Regression Bayesian Network and Its Applications

Siqi Nie, Meng Zheng, Qiang Ji

Deep directed generative models have attracted much attention recently due to their generative modeling nature and powerful data representation ability. In this paper, we review di…

cs.LG2015★ 1 cited

Latent Regression Bayesian Network for Data Representation

Siqi Nie, Qiang Ji

Deep directed generative models have attracted much attention recently due to their expressive representation power and the ability of ancestral sampling. One major difficulty of l…

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