Results 31 to 40 of about 7,181,199 (327)
Stein-Rule Estimation under an Extended Balanced Loss Function [PDF]
, 2007 This paper extends the balanced loss function to a more general set up. The ordinary least squares and Stein-rule estimators are exposed to this general loss function with quadratic loss structure in a linear regression model.
---, Shalabh +2 more
core +1 more source
Safety Maintains Lean Sustainability and Increases Performance through Fault Control
Applied Sciences, 2020 Almost every industrial and service enterprise adopts some form of Environmental Health and Safety (HSE) practices. However, there is no unified measurement implementation framework to resist losses exacerbated due to the “lack of safety precautions ...
Samia Elattar +2 more
doaj +1 more source
Loss-of-function analysis of EphA receptors in retinotectal mapping [PDF]
, 2004 Peer reviewedPublisher ...
DeChiara, Thomas M. +7 more
core +1 more source
Indium selenide: An insight into electronic band structure and surface excitations [PDF]
, 2017 We have investigated the electronic response of single crystals of indium selenide by means of angle-resolved photoemission spectroscopy, electron energy loss spectroscopy and density functional theory.
Agnoli, Stefano +12 more
core +4 more sources
Tomato Leaf Disease Identification Method Based on Improved YOLOX
Agronomy, 2023 In tomato leaf disease identification tasks, the high cost and consumption of deep learning-based recognition methods affect their deployment and application on embedded devices.
Wenbo Liu, Yongsen Zhai, Yu Xia
doaj +1 more source
Are Analysts' Loss Functions Asymmetric? [PDF]
Journal of Forecasting, 2006 ABSTRACTDespite displaying a statistically significant optimism bias, analysts' earnings forecasts are an important input to investors’ valuation models. Understanding the possible reasons for any bias is important if information is to be extracted from earnings forecasts and used optimally by investors. Extant research into the shape of analysts' loss
Clatworthy, Mark A. +2 more
openaire +3 more sources
DC Proximal Newton for Non-Convex Optimization Problems [PDF]
, 2015 We introduce a novel algorithm for solving learning problems where both the loss function and the regularizer are non-convex but belong to the class of difference of convex (DC) functions.
Flamary, Remi +2 more
core +4 more sources
Deep Learning Techniques for Vehicle Detection and Classification from Images/Videos: A Survey
Sensors, 2023 Detecting and classifying vehicles as objects from images and videos is challenging in appearance-based representation, yet plays a significant role in the substantial real-time applications of Intelligent Transportation Systems (ITSs).
Michael Abebe Berwo +7 more
doaj +1 more source
Retail commodity detection method based on location learnable visual center mechanism
物联网学报, 2023 To address the problem of low detection accuracy caused by the difficulty in effectively capturing significant and diversified feature information for packaging deformation and overlap products, a location learnable visual center (LLVC) mechanism was ...
Xiaohua LYU, Mingchen WEI, Libo LIU
doaj
, 2018 We describe a new framework for fitting jump models to a sequence of data. The key idea is to alternate between minimizing a loss function to fit multiple model parameters, and minimizing a discrete loss function to determine which set of model ...
Bemporad, A. +3 more
core +2 more sources