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researcher

Lili Su

22 papers hereh-index 181.9k citations46 works total

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

author position
  • first author13
  • middle author3
  • last author5

Across the 21 of 22 papers where every author was matched, so the position is known.

fields
  • cs.DC9
  • cs.LG9
  • cs.NI1
  • eess.SY1
  • q-bio.NC1
  • stat.ML1
same name
  • Lili Su — 5 papers, h 2
  • Lili Su — 5 papers, h 2
  • Lili Su — 5 papers, h 4
  • Lili Su — 4 papers, h 2
  • Lili Su — 4 papers, h 3
  • Lili Su — 2 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
20152023
most citedByzantine Multi-Agent Optimization: Part II

33 citations · 45 across the 12 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.DC2018

Collaboratively Learning the Best Option on Graphs, Using Bounded Local Memory

Lili Su, Martin Zubeldia, Nancy Lynch

We consider multi-armed bandit problems in social groups wherein each individual has bounded memory and shares the common goal of learning the best arm/option. We say an individual…

eess.SY2018

Finite-time Guarantees for Byzantine-Resilient Distributed State Estimation with Noisy Measurements

Lili Su, Shahin Shahrampour

This work considers resilient, cooperative state estimation in unreliable multi-agent networks. A network of agents aims to collaboratively estimate the value of an unknown vector…

cs.DC2018

Securing Distributed Gradient Descent in High Dimensional Statistical Learning

Lili Su, Jiaming Xu

We consider unreliable distributed learning systems wherein the training data is kept confidential by external workers, and the learner has to interact closely with those workers t…

cs.LG2018

Collaboratively Learning the Best Option, Using Bounded Memory

Lili Su, Martin Zubeldia, Nancy Lynch

We consider multi-armed bandit problems in social groups wherein each individual has bounded memory and shares the common goal of learning the best arm/option. We say an individual…

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