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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Renjun Hu
About me
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Posts
Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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Blog Post number 1
Published:
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portfolio
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publications
Lower Confidence Bound Policy for Optimization bounded Regression
Published in preparation, 2019
We study the problem where prediction objectives are some parameters in an optimization problem. We purpose a lower confidence bound policy such that the loss of optimization by predicting the parameters wrong has a tight bound. Moreoever, we purpose a tuning techiqnue such that the prediction by out method substantially outperforms than normal regression. We apply this algorithm to knapsack and network follow optmization problem, deriving an average of 2% decrement in expected optimization loss.
Consecutive Optimizer for XGBoost
Published in draft, 2019
Research work with Professor Teo Chung-Piaw in NUS Business School. We found that the optimization goal of the XGBoost algorithm well matches the conditions of consecutive optimizer. Based on this connection, We purpose a refined XGBoost algorithm that utilize the info from consecutive tree leaves to reduce the over-fitting issue. This algorithm has a O(KT[mn^2+dlogn]) time complexity that is tractable for prediction task of size 10-100K.
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Adaptive Rank Sampling with Robust Solution for Assortment Planning
Published in Manuscript, under revision, 2019
Research work with Professor Patrick Jaillet (MIT Operations Research Center) and Dr. Mai Anh (Singapore-MIT Alliance). In this paper, we show connections between parametric and rank-based choice models. We propose a new approach to sample ranks and update their distribution from population. We then propose a data-driven robust optimization model, i.e., likelihood robust optimization, for non-parametric assortment planning and we show how to solve the robust model in a tractable way. We provide experimental results using a real-like retail dataset, which shows the efficiency of our rank sampling approach and the tractability of our robust method.
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talks
teaching
Teaching Assistance
Published in National University of Singpaore, Department of Electrical and Computer Engineering, 2017
Teaching assistant for module INTRODUCTION TO PROGRAMMING WITH PYTHON AND C. Works included teaching tutorial sessions, grading homework, and managing the online teaching system (Coursemology).