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researcher

Dong Wang

10 papers hereh-index 131.1k citations41 works total

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

author position
  • middle author7
  • last author3

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.IR4
  • cs.LG4
  • cs.SI2
same name
  • Dong Wang — 40 papers, h 29
  • Dong Wang — 22 papers, h 7
  • Dong Wang — 19 papers, h 32
  • Dong Wang — 19 papers, h 10
  • Dong Wang — 16 papers, h 29
  • Dong Wang — 14 papers

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
20202024
most citedExtracting Attentive Social Temporal Excitation for Sequential Recommendation

10 citations · 20 across the 9 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2024

Personalized Binomial DAGs Learning with Network Structured Covariates

Boxin Zhao, Weishi Wang, Dingyuan Zhu +5

The causal dependence in data is often characterized by Directed Acyclic Graphical (DAG) models, widely used in many areas. Causal discovery aims to recover the DAG structure using…

cs.LG2022

Deep Page-Level Interest Network in Reinforcement Learning for Ads Allocation

Guogang Liao, Xiaowen Shi, Ze Wang +5

A mixed list of ads and organic items is usually displayed in feed and how to allocate the limited slots to maximize the overall revenue is a key problem. Meanwhile, modeling user…

cs.LG2021★ 3 cited

Multimodal Reward Shaping for Efficient Exploration in Reinforcement Learning

Mingqi Yuan, Mon-on Pun, Dong Wang +2

Maintaining the long-term exploration capability of the agent remains one of the critical challenges in deep reinforcement learning. A representative solution is to leverage reward…

cs.LG2020

eTREE: Learning Tree-structured Embeddings

Faisal M. Almutairi, Yunlong Wang, Dong Wang +2

Matrix factorization (MF) plays an important role in a wide range of machine learning and data mining models. MF is commonly used to obtain item embeddings and feature representati…

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