Results 91 to 100 of about 3,794 (238)

Generating Compressed Counterfactual Hard Negative Samples for Graph Contrastive Learning

CAAI 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, Hongxu Chen, Xiangyu Zhao, Sixiao Zhang, Xiangguo Sun, Qian Li, Hongzhi Yin, Guandong Xu   +7 more
wiley   +1 more source

A cooperative hyper-heuristic search framework [PDF]

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

NeuHH: A Neuromorphic-Inspired Hyper-Heuristic Framework for Solving the Capacitated Single-Allocation p-Hub Location Routing Problem

Vehicles
This paper introduces a novel neuromorphic-inspired hyper-heuristic framework (NeuHH) for solving the Capacitated Single-Allocation p-Hub Location Routing Problem (CSAp-HLRP), a challenging combinatorial optimization problem that jointly addresses hub ...
Kassem Danach, Hassan Harb, Semaan Amine, Mariem Belhor   +3 more
doaj   +1 more source

Investment Opportunities Forecasting: Extending the Grammar of a GP-based Tool [PDF]

, 2012
In this paper we present a new version of a GP financial forecasting tool, called EDDIE 8. The novelty of this version is that it allows the GP to search in the space of indicators, instead of using pre-specified ones.
Austin M., Binner J., Bouchachia A., Burke E., Cao L., Dempsey I., Edwards R., Hart E., Kampouridis M., Kim K., Koza J., Lam M., Marcek D., O'Neill M., Roh T., Sapankevych N., Tsang E., Tsang E., Özcan E.   +18 more
core   +3 more sources

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

IET 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

Acoustic indices are not useful for biodiversity research

Methods in Ecology and Evolution, EarlyView.
Abstract Biodiversity assessment using passive acoustic monitoring has historically been challenging due to the limited availability of multi‐species acoustic detectors. In this context, acoustic indices were introduced as an alternative way to represent species diversity in acoustic datasets.
Larissa S. M. Sugai, Cathleen Balantic, Dena J. Clink, Vijay Ramesh, Stefan Kahl, Holger Klinck, Connor M. Wood   +6 more
wiley   +1 more source

Hierarchical Differentiable Fluid Simulation

Computer 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, Arnaud Schoentgen, Damien Rioux‐Lavoie, Paul G. Kry, Derek Nowrouzezahrai   +4 more
wiley   +1 more source

Hyper-Heuristics and Scheduling Problems: Strategies, Application Areas, and Performance Metrics

IEEE Access
Scheduling problems, which involve allocating resources to tasks over specified time periods to optimize objectives, are crucial in various fields. This work presents hyper-heuristic applications for scheduling problems, analyzing 215 peer-reviewed ...
Alonso Vela, Gerardo Humberto Valencia-Rivera, Jorge M. Cruz-Duarte, Jose Carlos Ortiz-Bayliss, Ivan Amaya   +4 more
doaj   +1 more source

A Component Based Heuristic Search Method with Evolutionary Eliminations [PDF]

, 2008
Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. This paper presents a new component-based approach with evolutionary eliminations, for a nurse scheduling problem arising at a major UK ...
Ahuja R. K., Aickelin U., Aickelin U., Aickelin U., Anzai M., Bard J., Beliën J., Blau R., Bradley D., Burke E. K., Burke E. K., Burke E. K., Chen J. G., Dowsland K., Edmund K. Burke, Jingpeng Li, Kawanaka H., Li J., Lourenço H. R., Meyer auf'm Hofe H., Ross P., Sitompul D., Uwe Aickelin, Özcan E.   +23 more
core   +6 more sources

Adaptive Sampling for BRDF Acquisition

Computer Graphics Forum, EarlyView.
We propose a data‐driven adaptive sampling strategy that predicts the optimal sampling pattern and count for BRDF acquisition from a single image, reducing capture time while preserving quality. Abstract The bidirectional reflectance distribution function (BRDF) describes the ratio of incoming radiance to outgoing radiance for all possible pairs of ...
Behnaz Kavoosighafi, Saghi Hajisharif, Jonas Unger, Ehsan Miandji   +3 more
wiley   +1 more source