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Giulia Fanti

11 papers hereh-index 4189 citations15 works total

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

author position
  • middle author4
  • last author6

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.GT2
  • cs.CL1
  • cs.CR1
  • cs.CV1
  • cs.DC1
same name
  • Giulia Fanti — 6 papers, h 2
  • Giulia Fanti — 6 papers, h 4
  • Giulia Fanti — 4 papers, h 2
  • Giulia Fanti — 3 papers, h 2
  • Giulia Fanti — 3 papers, h 2
  • Giulia Fanti — 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
20232026
most citedMixture-of-Linear-Experts for Long-term Time Series Forecasting

7 citations · 9 across the 8 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

QuanText: Protecting Dataset-Level Secrets in Textual Data Sharing

Shuaiqi Wang, Zinan Lin, Giulia Fanti

Natural-language datasets support many downstream applications and research studies, but releasing text can reveal sensitive global properties of the underlying data source, such a…

cs.LG2024★ 1 cited

A Water Efficiency Dataset for African Data Centers

Noah Shumba, Opelo Tshekiso, Pengfei Li +2

Artificial intelligence (AI) computing and data centers consume large amounts of freshwater, both directly for cooling and indirectly for electricity generation. While most attenti…

cs.LG2024

Data Distribution Valuation

Xinyi Xu, Shuaiqi Wang, Chuan-Sheng Foo +2

Data valuation is a class of techniques for quantitatively assessing the value of data for applications like pricing in data marketplaces. Existing data valuation methods define a…

cs.LG2023★ 7 cited

Mixture-of-Linear-Experts for Long-term Time Series Forecasting

Ronghao Ni, Zinan Lin, Shuaiqi Wang +1

Long-term time series forecasting (LTSF) aims to predict future values of a time series given the past values. The current state-of-the-art (SOTA) on this problem is attained in so…

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