Results 61 to 70 of about 4,754 (207)

Surprise Marketing

open access: yesPsychology &Marketing, EarlyView.
ABSTRACT Surprise marketing, characterized by unexpected tactics such as blind boxes and spontaneous discounts, captivates consumers by sparking curiosity and participation. Despite increasing industry use, scholarly research remains fragmented and limited.
Xin‐Jean Lim   +2 more
wiley   +1 more source

Multi‐Agent Reinforcement Learning for Joint Police Patrol and Dispatch

open access: yesNaval Research Logistics (NRL), EarlyView.
ABSTRACT Police patrol units need to split their time between performing preventive patrol and being dispatched to serve emergency incidents. In the existing literature, patrol and dispatch decisions are often studied separately. We consider joint optimization of these two decisions to improve police operations efficiency and reduce response time to ...
Matthew Repasky, He Wang, Yao Xie
wiley   +1 more source

The power of expressed humility: Early stage investors' reaction to humble entrepreneurs

open access: yesStrategic Entrepreneurship Journal, EarlyView.
Abstract Research Summary We examine how entrepreneur‐expressed humility affects early stage investors' willingness to fund new ventures. In pitching contexts where investors rely on relational cues and implicit prototypes of entrepreneurs, we theorize three distinct pathways through which expressed humility shapes funding decisions. First, building on
Laurent Vilanova, Ivana Vitanova
wiley   +1 more source

Generating Compressed Counterfactual Hard Negative Samples for Graph Contrastive Learning

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Graph contrastive learning (GCL) relies on acquiring high‐quality positive and negative samples to learn the structural semantics of the input graph. Previous approaches typically sampled negative samples from the same training batch or an irrelevant external graph.
Haoran Yang   +7 more
wiley   +1 more source

A cooperative hyper-heuristic search framework [PDF]

open access: yesJournal of Heuristics, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ouelhadj, Djamila, Petrovic, S.
openaire   +3 more sources

Sub‐optimal Internet of Thing devices deployment using branch and bound method

open access: yesIET Networks, EarlyView.
The main contributions of this paper are (1) IoT network deployment problem formation as MILP problem to optimise the transmission among network nodes, and (2) New BB method with a machine learning function to reduce the computational complexity. Abstract The Internet of Thing (IoT) network deployments are widely investigated in 4G and 5G systems and ...
Haesik Kim
wiley   +1 more source

Toward Cost-Efficiency and Reduced Carbon Footprint: A Multi-Armed Bandit Hyper-Heuristic for Cloud Scheduling Problems

open access: yesIEEE Access
The urgent demand to reduce carbon emissions due to global warming has driven innovative approaches in cloud computing. This paper introduces the Hyper-Heuristic for Cloud Scheduling Problems (HHCSP), a hyper-heuristic designed to optimize tasks in cloud
Vinicius Renan De Carvalho   +1 more
doaj   +1 more source

‘But I can't preregister my research’: Improving the reproducibility and transparency of ecology and conservation with adaptive preregistration for model‐based research

open access: yesMethods in Ecology and Evolution, EarlyView.
Abstract Preregistration is an open science practice which aims to improve research transparency and mitigate questionable research practices, like cherry‐picking results. It helps protect against cognitive biases, like hindsight bias, that can influence how study outcomes are interpreted.
Elliot Gould   +9 more
wiley   +1 more source

A Column Generation Based Hyper-Heuristic to the Bus Driver Scheduling Problem

open access: yesDiscrete Dynamics in Nature and Society, 2015
Public transit providers are facing continuous pressure to improve service quality and reduce operating costs. Bus driver scheduling is among the most studied problems in this area.
Hong Li, Ying Wang, Shi Li, Sujian Li
doaj   +1 more source

Hierarchical Differentiable Fluid Simulation

open access: yesComputer Graphics Forum, EarlyView.
We introduce a two‐step algorithm that significantly reduces memory usage for solving control problems using differentiable fluid simulation techniques: our method first optimizes for bulk forces at reduced resolution, then refines local details over sub‐domains while maintaining differentiability. In trading runtime for memory, it enables optimization
Xiangyu Kong   +4 more
wiley   +1 more source

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