Results 21 to 30 of about 573 (57)
Accelerating Evolution Through Gene Masking and Distributed Search
, 2023 In building practical applications of evolutionary computation (EC), two optimizations are essential. First, the parameters of the search method need to be tuned to the domain in order to balance exploration and exploitation effectively.
Miikkulainen, Risto, Shahrzad, Hormoz
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On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments
, 2023 This work describes the investigation of neuromorphic computing-based spiking neural network (SNN) models used to filter data from sensor electronics in high energy physics experiments conducted at the High Luminosity Large Hadron Collider.
Bean, Alice +14 more
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, 2023 The main deficiency of the algorithms running on digital computers nowadays is their inability to change themselves during the execution. In line with this, the paper introduces the so-called replicated algorithms, inspired by the concept of developing a
Fister Jr., Iztok, Fister, Iztok
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Bio-inspired Optimization: metaheuristic algorithms for optimization
, 2020 In today's day and time solving real-world complex problems has become fundamentally vital and critical task. Many of these are combinatorial problems, where optimal solutions are sought rather than exact solutions.
Game, Pravin S +2 more
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Genetic Programming Across Domains: Leveraging Evolutionary Computation to Address Practical Problems [PDF]
Several modern technologies are based on Artificial Intelligence (AI) techniques, which are continuously studied and refined in many research fields. Among the sub-fields of AI, bio-inspired approaches, such as Genetic Programming (GP), have found great ...
ROVITO, LUIGI
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A Bandit Approach with Evolutionary Operators for Model Selection
This work formulates model selection as an infinite-armed bandit problem, namely, a problem in which a decision maker iteratively selects one of an infinite number of fixed choices (i.e., arms) when the properties of each choice are only partially known ...
Brégère, Margaux, Keisler, Julie
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DropELM:Fast Neural Network Regularization with Dropout and DropConnect [PDF]
, 2015 Iosifidis, Alexandros +2 more
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On the Robustness of Lexicase Selection to Contradictory Objectives
Lexicase and epsilon-lexicase selection are state of the art parent selection techniques for problems featuring multiple selection criteria. Originally, lexicase selection was developed for cases where these selection criteria are unlikely to be in ...
Dolson, Emily, Shahbandegan, Shakiba
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GraphGPT: Graph Instruction Tuning for Large Language Models
Graph Neural Networks (GNNs) have evolved to understand graph structures through recursive exchanges and aggregations among nodes. To enhance robustness, self-supervised learning (SSL) has become a vital tool for data augmentation.
Cheng, Suqi +7 more
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Colony-Enhanced Recurrent Neural Architecture Search: Collaborative Ant-Based Optimization
Crafting neural network architectures manually is a formidable challenge often leading to suboptimal and inefficient structures. The pursuit of the perfect neural configuration is a complex task, prompting the need for a metaheuristic approach such as ...
Elsaid, Abdelrahman
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