Results 91 to 100 of about 151,967 (341)
Multimode Oxide‐Based Optoelectronic Memtransistor for In‐Sensor Vision Processing
Advanced Functional Materials, EarlyView.A multimode optoelectronic memtransistor (OEMT) is demonstrated for vision explainable artificial intelligence (VXAI) hardware. By integrating optical sensing, electrical masking, and non‐volatile memory, the device enables key operations required for generating saliency information.
Min Gu Lee +10 more
wiley +1 more source
On Hyperparameter Search in Cluster Ensembles
CoRR, 2018 Quality assessments of models in unsupervised learning and clustering verification in particular have been a long-standing problem in the machine learning research. The lack of robust and universally applicable cluster validity scores often makes the algorithm selection and hyperparameter evaluation a tough guess.
Luzie Helfmann +3 more
openaire +2 more sources
Operando Tracking of Oxygen‐Vacancy Dynamics and Negative Capacitance in Ca‐Doped BiFeO3
Advanced Functional Materials, EarlyView.Operando electrochemical impedance spectroscopy, combined with electrocoloration, enables a direct correlation between real‐space ionic redistribution and the corresponding frequency‐domain electrical response. In lateral Ca‐doped BiFeO3 devices, time‐resolved impedance snapshots capture the evolution from bulk‐dominated mixed conduction to an ...
Jeonghun Suh +3 more
wiley +1 more source
An investigation on the use of Large Language Models for hyperparameter tuning in Evolutionary Algorithms [PDF]
GECCO CompanionHyperparameter optimization is a crucial problem in Evolutionary Computation. In fact, the values of the hyperparameters directly impact the trajectory taken by the optimization process, and their choice requires extensive reasoning by human operators ...
L. Custode +3 more
semanticscholar +1 more source
Hyperparameter tuning for SVR regressor.
, 2023 Hyperparameter tuning for SVR regressor.
Gabriel Cuevas (1475851) +5 more
core +1 more source
Advanced Functional Materials, EarlyView.Autonomous scanning probe microscopy and multi‐objective Bayesian optimization navigate a ternary (Al,Sc,B)N combinatorial library. Registered photoluminescence, electron‐probe compositional mapping, and X‐ray diffraction connect local electromechanical function to defect‐sensitive emission, composition, and crystal structure.
Yu Liu +12 more
wiley +1 more source
Metaheuristics Approach for Hyperparameter Tuning of Convolutional Neural Network
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)Deep learning is an artificial intelligence technique that has been used for various tasks. Deep learning performance is determined by its hyperparameter, architecture, and training (connection weight and bias).
Hindriyanto Purnomo +4 more
doaj +1 more source
Neural Processing LettersThis paper introduces an efficient real-coded genetic algorithm (RCGA) evolved for constrained real-parameter optimization. This novel RCGA incorporates three specially crafted evolutionary operators: Tournament Selection (RS) with elitism, Simulated ...
Fatima Zahrae El-Hassani +3 more
semanticscholar +1 more source
Hyperparameter Optimization in Machine Learning [PDF]
Found. Trends Mach. Learn.Hyperparameters are configuration variables controlling the behavior of machine learning algorithms. They are ubiquitous in machine learning and artificial intelligence and the choice of their values determines the effectiveness of systems based on these
Luca Franceschi +7 more
semanticscholar +1 more source
Metalearning for Hyperparameter Optimization
, 2022 This chapter describes various approaches for the hyperparameter optimization (HPO) and combined algorithm selection and hyperparameter optimization problems (CASH).
Joaquin Vanschoren +7 more
core +1 more source