Privacy-preserved learning from non-iid data in fog-assisted IoT: A federated learning approach
Privacy-preserved learning from non-iid data in fog-assisted IoT: A federated learning ...
Mohamed Abdel-Basset (5152634) +4 more
core
Demand Estimation with Text and Image Data
The RAND Journal of Economics, EarlyView.ABSTRACT We propose a demand estimation approach that leverages unstructured data to infer substitution patterns. Using pre‐trained deep learning models, we extract embeddings from product images and textual descriptions and incorporate them into a mixed logit demand model.
Giovanni Compiani +2 more
wiley +1 more source
Federated Privacy-Preserving Multi-Modal Deep Learning for Breast Cancer Diagnosis: A Physics-Aware Approach. [PDF]
Diagnostics (Basel)Al-Karawi ALS +2 more
europepmc +1 more source
Preemptive Entry and Technology Diffusion: The Market for Drive‐In Theaters
The RAND Journal of Economics, EarlyView.ABSTRACT This article studies entry preemption in new industries. We first test a key prediction of dynamic entry games: Entry preemption is most relevant in intermediate‐sized markets, where firms face highest uncertainty about future entry. Using US drive‐in theater market (1945–1957) data, we find robust evidence for this non‐monotonic relationship ...
Ricard Gil +3 more
wiley +1 more source
Enhancing pandemic surveillance and testing: a simulation modeling study utilizing german multicenter data with federated machine learning. [PDF]
Health Care Manag SciKempter S +8 more
europepmc +1 more source
SemiSFL: Split Federated Learning on Unlabeled and Non-IID Data
Federated Learning (FL) has emerged to allow multiple clients to collaboratively train machine learning models on their private data at the network edge.
Xu, Yang +5 more
core +1 more source
Output Quality, Productivity, and Demand: Evidence from the Chinese Steel Industry
The RAND Journal of Economics, EarlyView.ABSTRACT Unobserved objective output quality complicates the analysis of firm productivity and demand because higher‐quality products entail higher costs but offer greater consumption benefits. Using a panel of firms with output quality data, we decompose quantity‐based productivity into fundamental productivity and the costs of quality, and separate ...
Jing Li, Shengyu Li, Hongsong Zhang
wiley +1 more source
The Incidence of Coarse Certification: Evidence From the ENERGY STAR Program
The RAND Journal of Economics, EarlyView.ABSTRACT A coarse certification provides simple but incomplete information. Its rationale is to help consumers trade off dimensions of quality that are complex and lack salience. In imperfectly competitive markets, it may induce excess bunching at the certification requirement, crowd out quality, and facilitate price discrimination. Who will ultimately
Sébastien Houde
wiley +1 more source
Privacy-Preserving Hybrid GA-LSTM Ensemble for Typhoid Detection Using Optimised Clinical Feature Selection. [PDF]
BiomedicinesGasmi K +6 more
europepmc +1 more source
Mitigating policy uncertainty: What financial markets reveal about firm‐level lobbying
American Journal of Political Science, EarlyView.Abstract Elections can lead to substantial policy changes and, thus, are a significant source of risk. Firms can respond to such policy uncertainty by lobbying, but it is hard to quantify whether they do so and, if so, how much lobbying benefits them. We construct a new dataset and leverage investors’ expectations of variability in stock returns in the
Kristy Buzard +2 more
wiley +1 more source