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Researchers use machine learning algorithm to analyze consumer data（图）
machine learning algorithm analyze consumer data
2020/6/19
With electric vehicles making their way into the mainstream, building out the nationwide network of charging stations to keep them going will be increasingly important.Electric vehicles are considered...
Learning by Doing with Asymmetric Information: Evidence from Prosper
Prosper；Asymmetric Information
2015/9/21
Using peer-to-peer (P2P) lending as an example, we show that learning by doing plays an
important role in alleviating the information asymmetry between market players. Although
the P2P platform (Pro...
Imperfect Common Knowledge and Learning in the Swedish Kronor Market
Common Knowledge microeconomic
2015/9/21
We use both macroeconomic and microeconomic information to test for heterogeneous information
and the presence of learning on Swedish Kronor currency market. We further test
whether our findings imp...
Rationalizability,Learning and Equilibrium in Games With Strategic Complementarities
Rationalizability Learning Equilibrium Strategic Complementarities
2015/7/21
Rationalizability,Learning and Equilibrium in Games With Strategic Complementarities.
Adaptive and Sophisticated Learning in Repeated Normal Form Games
Adaptive Sophisticated Learning Repeated Normal
2015/7/21
Adaptive and Sophisticated Learning in Repeated Normal Form Games.
EVIDENCE ON LEARNING AND NETWORK EXTERNALITIES IN THE DIFFUSION OF HOME COMPUTERS
Evidence computer learning network externalities diffusion
2015/7/20
EVIDENCE ON LEARNING AND NETWORK EXTERNALITIES IN THE DIFFUSION OF HOME COMPUTERS.
Competitiveness presentation delivered in Dubai, United Arab Emirates.
This presentation draws on ideas from Professor Porter's articles and books, in particular, The Competitive Advantage of Nations (The Free Press, 1990), "Building the Microeconomic Foundations of Comp...
This presentation covers topics on social and economic development, including: competitve advantage of nations and regions, clusters, the social progress index, and creating shared value.
'My Bad!' How Internal Attribution and Ambiguity of Responsibility Affect Learning from Failure
Attitudes Failure Learning
2015/4/29
Learning in organizations is a key determinant of individual and organizational success, and one valuable source of this learning is prior failure. Previous research finds that although individuals ca...
Learning from Customers:Individual and Organizational Effects in Outsourced Radiological Services
Experience and Expertise Learning Health Care and Treatment
2015/4/23
The ongoing fragmentation of work has resulted in a narrowing of tasks into smaller pieces that can be sent outside the organization and, in many instances, around the world. This trend is shifting th...
National Science Foundation fiscal year 2016 budget request continues commitment to discovery, innovation and learning
National Science Foundation fiscal year 2016 budget request continues commitment to discovery innovation learning
2015/3/4
Today, National Science Foundation (NSF) Director France A. Córdova outlined President Obama's fiscal year (FY) 2016 budget request to Congress for NSF. The FY16 request calls for $7.7 bill...
Learning by Doing in a Multi-Product Manufacturing Environment: Product Variety, Customizations, and Overlapping Product Generations
a Multi-Product Manufacturing Environment Product Variety Customizations Overlapping Product Generations
2013/11/27
Extending research on organizational learning to multi-product environments is of particular importance given that the vast majority of products are manufactured in such environments. We investigate l...
Common Mistakes when Applying Computational Intelligence and Machine Learning to Stock Market modelling
Computational intelligence machine learning stock market equities automated stock tradin mistakes.
2012/9/17
For a number of reasons, computational intelligence and machine learning methods have been largely dismissed by the professional community. The reasons for this are numerous and ...
Adaptive Execution: Exploration and Learning of Price Impact
adaptive execution price impact reinforcement learning regret bound
2012/9/14
We consider a model in which a trader aims to maximize expected risk-adjusted profit while trading a single security. In our model, each price change isa linear combination of observed factors, impact...