Results 21 to 30 of about 211,846 (266)
Frugal Optimization for Cost-related Hyperparameters
, 2020 The increasing demand for democratizing machine learning algorithms calls for hyperparameter optimization (HPO) solutions at low cost. Many machine learning algorithms have hyperparameters which can cause a large variation in the training cost.
Huang, Silu, Wang, Chi, Wu, Qingyun
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No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL
, 2022 The performance of reinforcement learning (RL) agents is sensitive to the choice of hyperparameters. In real-world settings like robotics or industrial control systems, however, testing different hyperparameter configurations directly on the environment can be financially prohibitive, dangerous, or time consuming.
Wang, Han +9 more
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Nonlinear Hyperparameter Optimization of a Neural Network in Image Processing for Micromachines
Micromachines, 2021 Deep neural networks are widely used in the field of image processing for micromachines, such as in 3D shape detection in microelectronic high-speed dispensing and object detection in microrobots.
Mingming Shen +4 more
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Mathematics, 2022 Over the past few decades, convolutional neural networks (CNNs) have achieved outstanding results in addressing a broad scope of computer vision problems.
Rogeany Kanza +4 more
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Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations and Consistency [PDF]
, 2019 The Bayesian formulation of inverse problems is attractive for three primary reasons: it provides a clear modelling framework; means for uncertainty quantification; and it allows for principled learning of hyperparameters.
Dunlop, Matthew M. +2 more
core +4 more sources
Sensors, 2023 Pervasive computing, human–computer interaction, human behavior analysis, and human activity recognition (HAR) fields have grown significantly. Deep learning (DL)-based techniques have recently been effectively used to predict various human actions using
Shaik Jameer, Hussain Syed
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IEEE Access, 2023 Non-traumatic grief can be defined as, a complex process that includes emotional, physical, spiritual, social, and intellectual behaviors and responses through which individuals, families, and communities incorporate actual, anticipated, or perceived ...
Jacinto Mata-Vazquez +4 more
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Comparative Analysis of Transformers to Support Fine-Grained Emotion Detection in Short-Text Data
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Understanding a person’s mood and circumstances by way of sentiment or finer-grained emotion detection can play a significant role in AI systems and applications, such as in chat dialogue or reviews.
Robert H. Frye, David C. Wilson
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BrainOS: A Novel Artificial Brain-Alike Automatic Machine Learning Framework
Frontiers in Computational Neuroscience, 2020 Human intelligence is constituted by a multitude of cognitive functions activated either directly or indirectly by external stimuli of various kinds. Computational approaches to the cognitive sciences and to neuroscience are partly premised on the idea ...
Newton Howard +6 more
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Enhancing Load Prediction Accuracy using Optimized Support Vector Regression Models
Journal of Digital Food, Energy & Water Systems, 2023 This paper investigates the effect of Support Vector Regression hyperparameters optimization on electrical load prediction. Accurate and robust load prediction helps policy makers in the energy sector to make inform decision and reduce losses.
Abdulsemiu Olawuyi +3 more
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