Search Results - subject:"Learning process"

Flipped classroom goes sideways : reflections on active learning methodologies

Leão, Pablo; Coelho, Caio; Campana, Carla; Henriques … - In: REGE revista de gestão 30 (2023) 2, pp. 207-220

Persistent link: https://www.econbiz.de/10014279866

History-dependent monetary regimes : a lab experiment and a HENK model

Arifovic, Jasmina; Salle, Isabelle; Truong, Hung - 2023

Price-level targeting (PLT) is optimal under the fully-informed rational expectations (FIRE) benchmark but lacks empirical support. Given the hurdles to the implementation of macroeconomic field experiments, we utilize a laboratory group experiment - where expectations are elicited from human...

Persistent link: https://www.econbiz.de/10014280056

Bank choice, bank runs, and coordination in the presence of two banks

Arifovic, Jasmina; Jong, Johan de; Kopányi-Peuker, Anita - 2023

We investigate learning in a repeated bank choice game, where agents first choose a bank to deposit in and then decide to withdraw that deposit or not. This game has a single Nash equilibrium in pure strategies, characterized by all agents depositing in the bank that offers the highest return,...

Persistent link: https://www.econbiz.de/10014280066

Statistical Learning with Sublinear Regret of Propagator Models

Neuman, Eyal; Zhang, Yufei - 2023

We consider a class of learning problems in which an agent liquidates a risky asset while creating both transient price impact driven by an unknown convolution propagator and linear temporary price impact with an unknown parameter. We characterize the trader's performance as maximization of a...

Persistent link: https://www.econbiz.de/10014258369

A machine-learning based ConvLSTM architecture for NDVI forecasting

Ahmad, Rehaan; Yang, Brian; Ettlin, Guillermo; Berger, … - In: International transactions in operational research : a … 30 (2023) 4, pp. 2025-2048

Persistent link: https://www.econbiz.de/10014258978

Forgetful updating and stubborn decision-makers

Hu, Tai-Wei - In: Economic theory 75 (2023) 3, pp. 781-802

Persistent link: https://www.econbiz.de/10014259053

Deep Reinforcement Learning : A Study of Reinforcement Learning with Neural Networks in Industrial Automation

Iroshan, Asiri - 2023

Deep learning is a type of machine learning that has attracted a lot of attention in recent years because to its incredible achievements in a variety of applications like pattern recognition, audio recognition, computer vision, and natural language processing. Deep learning approaches can also...

Persistent link: https://www.econbiz.de/10014259318

Analysis of Motorcycle Engineering Vocational Skills Learning Model Based on Teaching Factory of Package C Students at Pkbm Berlian

Samsi - 2023

The purpose of this study was to determine the quality of the learning process, the determinants of process quality … significant influence on the acquisition of package C student learning outcomes; determinants of the quality of the learning … process are influenced by tutor factors, in addition to infrastructure, financing, leadership, and work climate; equality …

Persistent link: https://www.econbiz.de/10014259350

Learning Strategic Representations : Exploring the Effects of Taking a Strategy Course

Heshmati, Mana; Csaszar, Felipe A. - 2023

Despite the popularity of strategy courses and the fact that managers make consequential decisions using ideas they learn in such courses, few studies have examined the learning outcomes of taking a strategy course — a research gap most likely due to the methodological challenges of measuring...

Persistent link: https://www.econbiz.de/10014259704

State-of-The-Art Deep Learning Models are Superior for Time Series Forecasting and are Applied Optimally with Iterative Prediction Methods

murray, cathal john; Du Bois, Naomi; Hollywood, Lynsey; … - 2023

In recent years many new algorithms have been developed for applications in speech and image processing which may be repurposed for time series prediction. This paper presents a comprehensive comparative analysis of time series forecasting capabilities of eight such state-of-the-art algorithms...

Persistent link: https://www.econbiz.de/10014259788