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Profile
Kwang-Sung Jun
Assistant Professor, Computer Science | Member of the Graduate Faculty
Computer Science
Overview
Research
More
Collaboration
(19)
Hao Zhang
Mutual work: 3 Proposals
Collaboration Details
Clayton Morrison
Mutual work: 2 Proposals
Collaboration Details
Michael Chertkov
Mutual work: 1 Proposal
Collaboration Details
Larry Head
Mutual work: 1 Proposal
Collaboration Details
Mihai Surdeanu
Mutual work: 2 Proposals
Collaboration Details
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Grants
(2)
Adapting to Temporal Patterns in A/B Testing
Active
·
2025
·
$100K
·
External
Principal Investigator (PI)
temporal patterns,
adaptation,
behavioral analysis,
experimental design
CIF: Small: Theory and Algorithms for Efficient and Large-Scale Monte Carlo Tree Search
Active
·
2023
·
$599.2K
·
External
Principal Investigator (PI)
monte carlo,
algorithms,
efficiency,
theory,
large-scale
Publications
(51)
Recent
Adaptive Experimentation When You Can't Experiment
2024
limitations,
alternative methods,
statistical modeling,
decision making
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
2024
confidence intervals,
bandit algorithms,
generalized linear models,
statistical inference,
machine learning
Better-than-KL PAC-Bayes bounds
2024
bounds,
statistical learning,
risk management
APPENDIX A: PROBABILISTIC ASSESSMENT OF POSTFIRE DEBRIS-FLOW INUNDATION IN RESPONSE TO FORECAST RAINFALL
2024
debris flow,
postfire assessment,
rainfall forecast,
inundation
HAVER: Instance-Dependent Error Bounds for Maximum Mean Estimation and Applications to Q-Learning
2024
applications
Efficient low-rank matrix estimation, experimental design, and arm-set-dependent low-rank bandits
2024
experimental design,
bandit algorithms,
optimization,
machine learning
Fixing the Loose Brake: Exponential-Tailed Stopping Time in Best Arm Identification
2024
stochastic processes,
decision making,
statistical inference,
optimization,
machine learning
Minimum Empirical Divergence for Sub-Gaussian Linear Bandits
2024
linear bandits
Improved regret bounds of multinomial) logistic bandits via regret-to-confidence-set conversion
2024
bandit algorithms,
regret bounds,
logistic regression,
confidence sets
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization
2024
linear bandits,
adaptive methods
