搜索结果: 1-15 共查到“管理学 loss”相关记录35条 . 查询时间(0.31 秒)
Obesity,Weight Loss,and Employment Prospects:Evidence from a Randomized Trial
Obesity Weight Loss Employment Prospects Randomized Trial
2016/3/3
This study presents credible estimates for the causal effect of BMI growth on employment among the obese. By exploring random assignment of a weight-loss intervention based on monetary rewards, I prov...
On the Dynamics of a Finite Buffer Queue Conditioned on the Amount of Loss
Dynamics Finite Buffer Queue Conditioned Amount of Loss
2015/7/6
This paper is concerned with computing large deviations asymptotics for the loss process in a stylized queueing model that is fed by a Brownian input process. In addition, the dynamics of the queue, c...
Loss-averse测度下考虑政府补贴的双第三方回收再制造闭环供应链
风险规避 政府补贴 古诺竞争 收益费用共享契约
2015/7/27
以制造商、零售商及两个第三方回收商构成的再制造闭环供应链为背景,使用Loss-averse函数测度零售商的风险规避特性、古诺(Cournot)模型刻画第三方回收商的竞争特性,将政府补贴作为内生变量,构建了第三方回收再制造闭环供应链模型,分析了风险特性、政府补贴及竞争特性对供应链的影响,证明了收益费用共享契约可以克服双重边际效应和风险规避效应,优化loss-averse测度的考虑政府补贴的双第三方回...
Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families
SNML Exchangeability Exponential Family Online Learning Logarithmic Loss Bayesian Strategy Jeffreys Prior Fisher Information
2013/6/17
We study online learning under logarithmic loss with regular parametric models. Hedayati and Bartlett (2012b) showed that a Bayesian prediction strategy with Jeffreys prior and sequential normalized m...
Boosting with the Logistic Loss is Consistent
Boosting additive logistic regression coordinate descent convex analysis
2013/6/14
This manuscript provides optimization guarantees, generalization bounds, and statistical consistency results for AdaBoost variants which replace the exponential loss with the logistic and similar loss...
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions
Generalization Ability Online Learning Algorithms Pairwise Loss Functions
2013/6/14
In this paper, we study the generalization properties of online learning based stochastic methods for supervised learning problems where the loss function is dependent on more than one training sample...
Linear NDCG is used for measuring the performance of the Web content quality assessment in ECML/PKDD Discovery Challenge 2010. In this paper, we will prove that the DCG error equals a new pair-wise lo...
Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL
Minimax Multi-Task Learning a Generalized Loss-Compositional Paradigm MTL
2012/11/23
Since its inception, the modus operandi of multi-task learning (MTL) has been to minimize the task-wise mean of the empirical risks. We introduce a generalized loss-compositional paradigm for MTL that...
Total loss estimation using copula-based regression models
dependence modeling generalized linear model number of claims claim size policy loss
2012/11/23
We present a joint copula-based model for insurance claims and sizes. It uses bivariate copulae to accommodate for the dependence between these quantities. We derive the general distribution of the po...
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
Stochastic Dual Coordinate Ascent Methods Regularized Loss Minimization
2012/11/22
Stochastic Gradient Descent (SGD) has become popular for solving large scale supervised machine learning optimization problems such as SVM, due to their strong theoretical guarantees. While the closel...
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
Stochastic Dual Coordinate Ascent Methods Regularized Loss Minimization
2012/11/22
Stochastic Gradient Descent (SGD) has become popular for solving large scale supervised machine learning optimization problems such as SVM, due to their strong theoretical guarantees. While the closel...
The Pythagorean Won-Loss Formula and Hockey: A Statistical Justification for Using the Classic Baseball Formula as an Evaluative Tool in Hockey
The Pythagorean Won-Loss Formula Hockey Statistical Justification Baseball Formula Evaluative Tool
2012/9/17
Originally devised for baseball, the Pythagorean Won-Loss formula estimates the percentage of games a team should have won at a particular point in a season. For decades, this formula had no mathemat...
Loss-sensitive Training of Probabilistic Conditional Random Fields
Loss-sensitive Training Probabilistic Conditional Random Fields
2011/7/19
We consider the problem of training probabilistic conditional random fields (CRFs) in the context of a task where performance is measured using a specific loss function. While maximum likelihood is th...
Classification Loss Function for Parameter Ensembles in Bayesian Hierarchical Models
Classification Loss Function Parameter Ensembles Bayesian Hierarchical Models
2011/6/20
Our perspective in this paper follows the framework adopted by Lin et al. (2006), who intro-
duced several loss functions for the identi cation of the elements of a parameter ensemble that
represent...
Analytic Loss Distributional Approach Model for Operational Risk from the alpha-Stable Doubly Stochastic Compound Processes and Implications for Capital Allocation
Operational Risk Loss Distributional Approach Doubly stochastic Poisson Process -Stable Basel II Solvency II
2011/3/25
Under the Basel II standards, the Operational Risk (OpRisk) advanced measurement approach is not prescriptive regarding the class of statistical model utilised to undertake capital estimation. It has ...