dual averaging
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2021 ◽  
Author(s):  
Zhong Chen ◽  
Zhide Fang ◽  
Victor Sheng ◽  
Andrea Edwards ◽  
Kun Zhang




Author(s):  
David Müller ◽  
Yurii Nesterov ◽  
Vladimir Shikhman

We derive new prox-functions on the simplex from additive random utility models of discrete choice. They are convex conjugates of the corresponding surplus functions. In particular, we explicitly derive the convexity parameter of discrete choice prox-functions associated with generalized extreme value models, and specifically with generalized nested logit models. Incorporated into subgradient schemes, discrete choice prox-functions lead to a probabilistic interpretations of the iteration steps. As illustration, we discuss an economic application of discrete choice prox-functions in consumer theory. The dual averaging scheme from convex programming adjusts demand within a consumption cycle.



Author(s):  
Cong Wang ◽  
Shengyuan Xu ◽  
Deming Yuan ◽  
Yuming Chu ◽  
Zhengqiang Zhang




2021 ◽  
Author(s):  
Yang Liu ◽  
Zhu Wang ◽  
Chaowen Zhu ◽  
Dong Wang ◽  
Wei Wang


Author(s):  
Dongyu Han ◽  
Kun Liu ◽  
Henrik Sandberg ◽  
Senchun Chai ◽  
Yuanqing Xia




2020 ◽  
Vol 35 (4) ◽  
pp. 741-766
Author(s):  
Conghui Tan ◽  
Yuqiu Qian ◽  
Shiqian Ma ◽  
Tong Zhang


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