IEOR 8100-001: Learning and Optimization for Sequential Decision Making

IEOR 8100-001: Learning and Optimization for Sequential Decision Making 04/06/16 Lecture 21: Learning and optimization for sequential decision making

IEOR 8100-001: Learning and Optimization for Sequential Decision Making 02/03/16 Lecture 5: Thomposon Sampling (part II): Regret bounds proofs

We describe the main technical difficulties in the proof for TS algorithm as compared to the UCB algorithm. In UCB algorithm, the suboptimal arm 2 will be played at time t, if its UCB value is higher, i.e. if UCB2,t−1 > UCB1,t−1. If we have pulled arm 2 for some amount of times Ω( log(T ) ∆2 ), then with a high probability this will not happen. This is because after n2,t ≥ Ω(log(T )/∆), using c...

A Random Forest Classifier based on Genetic Algorithm for Cardiovascular Diseases Diagnosis (RESEARCH NOTE)

Machine learning-based classification techniques provide support for the decision making process in the field of healthcare, especially in disease diagnosis, prognosis and screening. Healthcare datasets are voluminous in nature and their high dimensionality problem comprises in terms of slower learning rate and higher computational cost. Feature selection is expected to deal with the high dimen...

Optimizing Red Blood Cells Consumption Using Markov Decision Process

In healthcare systems, one of the important actions is related to perishable products such as red blood cells (RBCs) units that its consumption management in different periods can contribute greatly to the optimality of the system. In this paper, main goal is to enhance the ability of medical community to organize the RBCs units’ consumption in way to deliver the unit order timely with a focus ...

Matrix Sequential Hybrid Credit Scorecard Based on Logistic Regression and Clustering

The Basel II Accord pointed out benefits of credit risk management through internal models to estimate Probability of Default (PD). Banks use default predictions to estimate the loan applicants’ PD. However, in practice, PD is not useful and banks applied credit scorecards for their decision making process. Also the competitive pressures in lending industry forced banks to use profit scorecards...