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Xin Guo

15 papers hereh-index 8134 citations21 works total

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

author position
  • first author1
  • middle author9
  • last author4

Across the 14 of 15 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • math.OC3
  • q-fin.MF2
  • stat.ML2
  • cs.AI1
  • cs.GT1
same name
  • Xin Guo — 26 papers, h 16
  • Xin Guo — 12 papers, h 6
  • Xin Guo — 10 papers, h 3
  • Xin Guo — 9 papers, h 18
  • Xin Guo — 9 papers, h 3
  • Xin Guo — 8 papers, h 6

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
20192026
most citedNonzero-sum stochastic games and mean-field games with impulse controls

11 citations · 25 across the 15 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

q-fin.MF2023

Risk of Transfer Learning and its Applications in Finance

Haoyang Cao, Haotian Gu, Xin Guo +1

Transfer learning is an emerging and popular paradigm for utilizing existing knowledge from previous learning tasks to improve the performance of new ones. In this paper, we propos…

q-fin.PM2023

Transfer Learning for Portfolio Optimization

Haoyang Cao, Haotian Gu, Xin Guo +1

In this work, we explore the possibility of utilizing transfer learning techniques to address the financial portfolio optimization problem. We introduce a novel concept called "tra…

cs.LG2023★ 2 cited

Feasibility of Transfer Learning: A Mathematical Framework

Haoyang Cao, Haotian Gu, Xin Guo

Transfer learning is a popular paradigm for utilizing existing knowledge from previous learning tasks to improve the performance of new ones. It has enjoyed numerous empirical succ…

cs.LG2023

Feasibility and Transferability of Transfer Learning: A Mathematical Framework

Haoyang Cao, Haotian Gu, Xin Guo +1

Transfer learning is an emerging and popular paradigm for utilizing existing knowledge from previous learning tasks to improve the performance of new ones. Despite its numerous emp…

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