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Titlebook: Artificial Intelligence and Soft Computing; 21st International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2023

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樓主: aspirant
21#
發(fā)表于 2025-3-25 06:26:15 | 只看該作者
Multi-objective Bayesian Optimization for?Neural Architecture Searchod is applied to combine classification accuracy with network size on two benchmark datasets here. The results indicate that MO-BayONet is able to outperform an available genetic algorithm based approach.
22#
發(fā)表于 2025-3-25 07:57:37 | 只看該作者
Multilayer Perceptrons with?Banach-Like Perceptrons Based on?Semi-inner Products – About Approximatiroducts are related either to uniformly convex or to reflexive Banach-spaces. Most famous examples of uniformly convex Banach spaces are the spaces . and . for .. The result is valid for all discriminatory activation functions including the sigmoid and the . activation.
23#
發(fā)表于 2025-3-25 12:36:51 | 只看該作者
24#
發(fā)表于 2025-3-25 18:15:07 | 只看該作者
25#
發(fā)表于 2025-3-25 22:29:40 | 只看該作者
A Fast Learning Algorithm for?the?Multi-layer Neural Networks boosts the algorithm significantly due to the elimination of the computation of the square root. In a classic variant scaled rotations utilize so-called scale factors — .. It turns out that the scale factors can be omitted during the computation which boosts the overall algorithm performance even
26#
發(fā)表于 2025-3-26 04:02:40 | 只看該作者
A New Computational Approach to?the?Levenberg-Marquardt Learning Algorithmns to effectively reduce the high computational load of this algorithm. Detailed parallel neural network computations are explicitly discussed. Additionally obtained acceleration is shown based on a few test problems.
27#
發(fā)表于 2025-3-26 05:05:23 | 只看該作者
28#
發(fā)表于 2025-3-26 10:52:51 | 只看該作者
An Empirical Study of?Adversarial Domain Adaptation on?Time Series Datan various time series domains. Although several domain-adversarial models have been proposed in the past, there is a lack of empirical results with different types of time series. This paper provides an empirical analysis with multiple models, datasets and evaluation objectives. Two models known fro
29#
發(fā)表于 2025-3-26 14:50:03 | 只看該作者
Human-AI Collaboration to?Increase the?Perception of?VRsic functionality for immersing yourself in a virtual environment. In this paper, we propose a human-AI collaboration for analyzing the newly generated images that can be used for creating worlds. The presented method is based on analyzing different scenes (from simulation and real environment) usin
30#
發(fā)表于 2025-3-26 18:24:57 | 只看該作者
Portfolio Transformer for?Attention-Based Asset Allocationeights. Any errors made during the forecasting step reduce the accuracy of the asset weightings, and hence the profitability of the overall portfolio. The . (PT) network, introduced here, circumvents the need to predict asset returns and instead directly optimizes the Sharpe ratio, a risk-adjusted p
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