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researcher

Yanning Shen

30 papers hereh-index 222k citations88 works total

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

author position
  • first author7
  • middle author13
  • last author9

Across the 29 of 30 papers where every author was matched, so the position is known.

fields
  • cs.LG15
  • cs.IT5
  • stat.ML4
  • eess.SP2
  • cs.AI1
  • cs.SI1
same name
  • Yanning Shen — 6 papers, h 3
  • Yanning Shen — 6 papers, h 4
  • Yanning Shen — 4 papers, h 3
  • Yanning Shen — 2 papers, h 1
  • Yanning Shen — 2 papers, h 4
  • Yanning Shen — 2 papers, h 2

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
20122025
most citedKernel-Based Structural Equation Models for Topology Identification of Directed Networks

98 citations · 527 across the 30 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.LG2023★ 2 cited

Personalized Online Federated Learning with Multiple Kernels

Pouya M. Ghari, Yanning Shen

Multi-kernel learning (MKL) exhibits well-documented performance in online non-linear function approximation. Federated learning enables a group of learners (called clients) to tra…

cs.LG2023

Model Extraction Attacks Against Reinforcement Learning Based Controllers

Momina Sajid, Yanning Shen, Yasser Shoukry

We introduce the problem of model-extraction attacks in cyber-physical systems in which an attacker attempts to estimate (or extract) the feedback controller of the system. Extract…

cs.LG2023★ 1 cited

FairGAT: Fairness-aware Graph Attention Networks

O. Deniz Kose, Yanning Shen

Graphs can facilitate modeling various complex systems such as gene networks and power grids, as well as analyzing the underlying relations within them. Learning over graphs has re…

cs.LG2023★ 1 cited

Fairness-Aware Graph Filter Design

O. Deniz Kose, Yanning Shen, Gonzalo Mateos

Graphs are mathematical tools that can be used to represent complex real-world systems, such as financial markets and social networks. Hence, machine learning (ML) over graphs has…

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