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Decision Sciences
Decision Sciences 논문 리뷰
Decision Sciences 분야 주요 연구 논문을 연구 동기·방법·결과로 구조화한 AI 논문 리뷰 목록입니다.
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필터
5,642개의 결과
A Machine Learning Model for Stock Market Prediction
Osman Hegazy, Omar S. Soliman 외 1명
arXiv (Cornell University)
|
2014
|
119 회 인용
Efficient Optimal Learning for Contextual Bandits
Miroslav Dudı́k, Daniel Hsu 외 5명
arXiv (Cornell University)
|
2011
|
119 회 인용
Optimization, Learning, and Games with Predictable Sequences
Sasha Rakhlin, Karthik Sridharan
arXiv (Cornell University)
|
2013
|
118 회 인용
Reinforcement and Imitation Learning via Interactive No-Regret Learning
Stéphane Ross, J. Andrew Bagnell
arXiv (Cornell University)
|
2014
|
118 회 인용
Exploring multi-dimensional spaces: a Comparison of Latin Hypercube and Quasi Monte Carlo Sampling Techniques
Sergei Kucherenko, Daniel Albrecht 외 1명
arXiv (Cornell University)
|
2015
|
117 회 인용
Predicting the direction of stock market prices using random forest
Luckyson Khaidem, Snehanshu Saha 외 1명
arXiv (Cornell University)
|
2016
|
117 회 인용
To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making
Zana Buçinca, Maja Barbara Malaya 외 1명
arXiv (Cornell University)
|
2021
|
117 회 인용
Approximate Revenue Maximization with Multiple Items
Sergiu Hart, Noam Nisan
2012
|
116 회 인용
Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases
Gerhard Weikum, Xin Dong 외 2명
arXiv (Cornell University)
|
2020
|
115 회 인용
Why is Posterior Sampling Better than Optimism for Reinforcement Learning?
Ian Osband, Benjamin Van Roy
arXiv (Cornell University)
|
2016
|
115 회 인용
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