Results 71 to 80 of about 24,182 (212)
, 2017 We consider stochastic programs where the distribution of the uncertain parameters is only observable through a finite training dataset. Using the Wasserstein metric, we construct a ball in the space of (multivariate and non-discrete) probability ...
Esfahani, Peyman Mohajerin, Kuhn, Daniel
core +1 more source
Conditional Generative Modeling for Enhanced Credit Risk Management in Supply Chain Finance
Naval Research Logistics (NRL), EarlyView.ABSTRACT The rapid expansion of cross‐border e‐commerce (CBEC) has created significant opportunities for small‐ and medium‐sized sellers, yet financing remains a critical challenge due to their limited credit histories. Third‐party logistics (3PL)‐led supply chain finance (SCF) has emerged as a promising solution, leveraging in‐transit inventory as ...
Qingkai Zhang, L. Jeff Hong, Houmin Yan
wiley +1 more source
Learning with a Wasserstein loss [PDF]
, 2017 Learning to predict multi-label outputs is challenging, but in many problems there is a natural metric on the outputs that can be used to improve predictions.In this paper we develop a loss function for multi-label learning, based on the Wasserstein ...
Araya-Polo, Mauricio +4 more
core
Distributional Reinforcement Learning with Quantile Regression
, 2017 In reinforcement learning an agent interacts with the environment by taking actions and observing the next state and reward. When sampled probabilistically, these state transitions, rewards, and actions can all induce randomness in the observed long-term
Bellemare, Marc G. +3 more
core +1 more source
People and Nature, EarlyView.Abstract High aggregate levels of wildlife consumption in cities in Central Africa highlight the need for solutions that balance wildlife protection, local livelihoods and the relational values between people and nature. This study explores the impacts of demand‐ and supply‐side interventions on wild meat consumption through two randomized control ...
Abdoulaye Cisse +2 more
wiley +1 more source
{Euclidean, metric, and Wasserstein} gradient flows: an overview
Bulletin of Mathematical Sciences, 2017 This is an expository paper on the theory of gradient flows, and in particular of those PDEs which can be interpreted as gradient flows for the Wasserstein metric on the space of probability measures (a distance induced by optimal transport). The starting point is the Euclidean theory, and then its generalization to metric spaces, according to the work
openaire +2 more sources
Dynamic Adaptive Label Assignment for Tiny Object Detection in Remote Sensing Images
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT With the development of unmanned aerial vehicle and satellite technology, the application of tiny object detection in remote sensing images is becoming increasingly widespread. Although significant progress has been made in the accuracy and speed of object detection in recent years, performance declines sharply when general object detectors ...
Shuohao Shi, Qiang Fang, Xin Xu
wiley +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Intrinsic motivation serves as the predominant paradigm of exploration in reinforcement learning. In pursuit of an informative and robust state representation, the behavioural metric groups behaviourally equivalent states together, which share the same single‐step reward and transition distribution.
Anjie Zhu +3 more
wiley +1 more source
Engineering Reports, 2023 The penetration of wind turbines in the power grid is increasing rapidly. Still, the wind turbine output power has uncertainty, leading to poor grid reliability, affecting the grid's dispatching plan, and increasing the total cost.
Gengrui Chen +5 more
doaj +1 more source