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A cost–based analysis for risk–averse explore–then–commit finite–time bandits
Ali Yekkehkhany
, Ebrahim Arian
,
Rakesh Nagi
,
Ilan Shomorony
Industrial and Enterprise Systems Engineering
Electrical and Computer Engineering
Coordinated Science Lab
Siebel School of Computing and Data Science
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Keyphrases
Bandits
100%
Regret
100%
Exploration Phase
75%
Hyperparameters
50%
Linear Combination
25%
Minimum number
25%
Most Probable
25%
Number of Experiments
25%
Confidence Level
25%
Finite number
25%
Minimum Value
25%
Optimal number
25%
Expected Payoff
25%
Risk Aversion
25%
Value-based Approach
25%
Exploration-exploitation
25%
Robust Behavior
25%
Personalized Care
25%
Multi-arm Bandit
25%
Multi-armed Bandit Problem
25%
Bandit Algorithms
25%
Exploitation Costs
25%
Healthcare Investment
25%
Regret Function
25%
Mathematics
Upper Bound
100%
Linear Combination
50%
Optimal Number
50%
Finite Number
50%
Confidence Level
50%
Risk Aversion
50%
Healthcare
50%
Computer Science
Leaning Parameter
100%
Linear Combination
50%
Confidence Level
50%
Health Care
50%