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researcher

Ziqi Zhao

4 papers here

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

author position
  • first author2
  • middle author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.IR1
  • cs.LG1
  • cs.NI1
  • cs.RO1
ORCID 0009-0003-6776-3029
same name
  • Ziqi Zhao — 3 papers
  • Ziqi Zhao — 3 papers
  • Ziqi Zhao — 1 paper, h 4
  • Ziqi Zhao — 1 paper
  • Ziqi Zhao — 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
20222024
most citedInterpretation of Time-Series Deep Models: A Survey

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

collaborators

4 papers

cs.RO2024

Omni Differential Drive for Simultaneous Reconfiguration and Omnidirectional Mobility of Wheeled Robots

Ziqi Zhao, Peijia Xie, Max Q. -H. Meng

Wheeled robots are highly efficient in human living environments. However, conventional wheeled designs, limited by degrees of freedom, struggle to meet varying footprint needs and…

cs.NI2023

FIS-ONE: Floor Identification System with One Label for Crowdsourced RF Signals

Weipeng Zhuo, Ka Ho Chiu, Jierun Chen +4

Floor labels of crowdsourced RF signals are crucial for many smart-city applications, such as multi-floor indoor localization, geofencing, and robot surveillance. To build a predic…

cs.LG2023★ 3 cited

Interpretation of Time-Series Deep Models: A Survey

Ziqi Zhao, Yucheng Shi, Shushan Wu +3

Deep learning models developed for time-series associated tasks have become more widely researched nowadays. However, due to the unintuitive nature of time-series data, the interpr…

cs.IR2022★ 1 cited

Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation

Chang Meng, Ziqi Zhao, Wei Guo +6

Multi-types of behaviors (e.g., clicking, adding to cart, purchasing, etc.) widely exist in most real-world recommendation scenarios, which are beneficial to learn users' multi-fac…

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