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Gi-Soo Kim

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

fields
  • stat.ML3

identity via Semantic Scholar / OpenAlex

most citedContextual Multi-armed Bandit Algorithm for Semiparametric Reward Model

6 citations · 6 across the 2 of their papers we have counts for

collaborators

3 papers

stat.ML2022

Semi-Parametric Contextual Bandits with Graph-Laplacian Regularization

Young-Geun Choi, Gi-Soo Kim, Seunghoon Paik +1

Non-stationarity is ubiquitous in human behavior and addressing it in the contextual bandits is challenging. Several works have addressed the problem by investigating semi-parametr…

stat.ML2019

Doubly-Robust Lasso Bandit

Gi-Soo Kim, Myunghee Cho Paik

Contextual multi-armed bandit algorithms are widely used in sequential decision tasks such as news article recommendation systems, web page ad placement algorithms, and mobile heal…

stat.ML2019★ 6 cited

Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model

Gi-Soo Kim, Myunghee Cho Paik

Contextual multi-armed bandit (MAB) algorithms have been shown promising for maximizing cumulative rewards in sequential decision tasks such as news article recommendation systems,…

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