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IEEE Computational Intelligence Society Publications IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11
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IEEE Symposium Series on Computational Intelligence IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11
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Call for Papers for Journal Special Issues IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11
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Share Your Preprint Research with the World! IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11
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Advancing Medicine With Computational Intelligence [Editor's Remarks] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11 Chuan-Kang Ting
Computational Intelligence (CI) techniques have succeeded in various aspects of our daily lives, such as facial recognition, object detection, personalized recommendations, chatbots, and autonomous driving. Among these applications, medicine is of paramount importance. In particular, CI is expected to enhance diagnosis, medical treatment, medication, drug discovery, and healthcare, thereby improving
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Time Flies [President's Message] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11 Yaochu Jin
Time indeed flies. This is no longer just a saying, but a reality, when I was again reminded by our Editor-in-Chief to complete my President's message for the August Issue of the IEEE Computational Intelligence Magazine.
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A Perspective on Scalable AI on High-Performance Computing and Leadership Class Supercomputing Facilities [Industrial and Governmental Activities] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11 Massimiliano Lupo Pasini
Many scientific applications that support the mission of the US Department of Energy (US-DoE) require modeling complex engineering and/or physical systems [1], [2]. Examples of such complex systems arise from: (a) materials science to develop new compounds with exceptional mechanical and thermodynamical properties (e.g., resistance to mechanical stresses and high temperatures) [3], [4], [5], (b) structural
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CIS Publication Spotlight [Publication Spotlight] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11 Yongduan Song, Dongrui Wu, Carlos A. Coello Coello, Georgios N. Yannakakis, Yiu-ming Cheung, Hussein Abbass
“The strengthening and the weakening of synaptic strength in existing Bienenstock-Cooper-Munro (BCM) learning rule are determined by a long-term potentiation (LTP) sliding modification threshold and the afferent synaptic activities. However, synaptic long-term depression (LTD) even affects low-active synapses during the induction of synaptic plasticity, which may lead to information loss. Biological
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Rearrange Anatomy Inputs Like LEGO Bricks: Applying InSSS-P and a Mobile-Dense Hybrid Network to Distill Vascular Significance From Retina OCT-Angiography IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11 Kao-Jung Chang, Tai-Chi Lin, Chih-Chien Hsu, De-Kuang Hwang, Shih-Jen Chen, Shih-Hwa Chiou, Cheng-Yi Li, Ling Chen, Cherng-Ru Hsu, Wei-Hao Chang
Medical deep neural networks (DNNs) trained upon coarse image inputs are inherently insensible to fine-grained anatomic features. To enhance DNN perception on delicate microvascular structures, we proposed using a straightforward angiographic mobile-dense hybrid network (AMDenseNet) in tandem with a flexible input split, suppression, and swap perturbation (InSSS-P) framework to perform explainable
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Automatically Evolving Interpretable Feature Vectors Using Genetic Programming for an Ensemble Classifier in Skin Cancer Detection IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11 Qurrat Ul Ain, Harith Al-Sahaf, Bing Xue, Mengjie Zhang
Early skin cancer diagnosis saves lives as the disease can be successfully treated through complete excision. Computer-aided diagnosis methods are developed using artificial intelligence techniques to help earlier detection and identify hidden causes leading to cancers in skin lesion images. In skin cancer image classification problems, an ensemble of classifiers has demonstrated better classification
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A Comprehensive Survey on Heart Sound Analysis in the Deep Learning Era IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11 Zhao Ren, Yi Chang, Thanh Tam Nguyen, Yang Tan, Kun Qian, Björn W. Schuller
Heart sound auscultation has been applied in clinical usage for early screening of cardiovascular diseases. Due to the high demand for auscultation expertise, automatic auscultation can help with auxiliary diagnosis and reduce the burden of training professional clinicians. Nevertheless, there is a limit to classic machine learning’s performance improvement in the era of Big Data. Deep learning has
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Evolutionary Retrosynthetic Route Planning [Research Frontier] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11 Yan Zhang, Xiao He, Shuanhu Gao, Aimin Zhou, Hao Hao
Molecular retrosynthesis is a significant and complex problem in the field of chemistry, however, traditional manual synthesis methods not only need well-trained experts but also are time-consuming. With the development of Big Data and machine learning, artificial intelligence (AI) based retrosynthesis is attracting more attention and has become a valuable tool for molecular retrosynthesis. At present
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Mimer: A Web-Based Tool for Knowledge Discovery in Multi-Criteria Decision Support [Application Notes] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11 Henrik Smedberg, Sunith Bandaru, Maria Riveiro, Amos H.C. Ng
Practitioners of multi-objective optimization currently lack open tools that provide decision support through knowledge discovery. There exist many software platforms for multi-objective optimization, but they often fall short of implementing methods for rigorous post-optimality analysis and knowledge discovery from the generated solutions. This paper presents Mimer, a multi-criteria decision support
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Conference Calendar [Conference Calendar] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-07-11 Leandro Lei Minku, Liyan Song
* 2024 IEEE Conference on Games (CoG 2024)
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CIS Publication Spotlight [Publication Spotlight] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-08 Yongduan Song, Dongrui Wu, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yiu-Ming Cheung, Hussein Abbass
Presents a brief summary of new publications in the area of computational intelligence.
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Recent Developments in Recommender Systems: A Survey [Review Article] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-08 Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, Erik Cambria
In this technical survey, the latest advancements in the field of recommender systems are comprehensively summarized. The objective of this study is to provide an overview of the current state-of-the-art in the field and highlight the latest trends in the development of recommender systems. It starts with a comprehensive summary of the main taxonomy of recommender systems, including personalized and
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An Objective Space Constraint-Based Evolutionary Method for High-Dimensional Feature Selection [Research Frontier] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-08 Fan Cheng, Rui Zhang, Zhengfeng Huang, Jianfeng Qiu, Mingming Xia, Lei Zhang
Evolutionary algorithms (EAs) have shown their competitiveness in solving the problem of feature selection. However, limited by their encoding scheme, most of them face the challenge of “curse of dimensionality”. To address the issue, in this paper, an objective space constraint-based evolutionary algorithm, named OSC-EA, is proposed for high-dimensional feature selection (HDFS). Although the decision
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Diffusion Model-Based Multiobjective Optimization for Gasoline Blending Scheduling IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-08 Wenxuan Fang, Wei Du, Renchu He, Yang Tang, Yaochu Jin, Gary G. Yen
Gasoline blending scheduling uses resource allocation and operation sequencing to meet a refinery’s production requirements. The presence of nonlinearity, integer constraints, and a large number of decision variables adds complexity to this problem, posing challenges for traditional and evolutionary algorithms. This paper introduces a novel multiobjective optimization approach driven by a diffusion
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Encoding Distributional Soft Actor-Critic for Autonomous Driving in Multi-Lane Scenarios [Research Frontier] [Research Frontier] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Jingliang Duan, Yangang Ren, Fawang Zhang, Jie Li, Shengbo Eben Li, Yang Guan, Keqiang Li
This paper proposes a new reinforcement learning (RL) algorithm, called encoding distributional soft actor-critic (E-DSAC), for decision-making in autonomous driving. Unlike existing RL-based decision-making methods, E-DSAC is suitable for situations where the number of surrounding vehicles is variable and eliminates the requirement for manually pre-designed sorting rules, resulting in higher policy
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Don't Play Games, Optimize [President's Message] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Yaochu Jin
When I give a talk about evolutionary machine learning, one question I often expect is why I use an evolutionary algorithm to optimize the hyperparameters and structure of a neural network, rather than using a reinforcement learning algorithm. A quick answer might be, well, I am an evolutionary computation guy. I know this is a sloppy answer. Often, I attempt to explain the potential benefits of using
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IEEE Fellows–Class of 2024 [Society Briefs] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Gary G. Yen
Presents a listing of CIS members who were elevated to the status of IEEE Fellow.
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Call for Participation: IEEE Conference on Artificial Intelligence IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05
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Newly Elected CIS Administrative Committee Members [Society Briefs] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Yaochu Jin
Pauline Haddow is a Professor in the Department of Computer Science at the Norwegian University of Science and Technology (NTNU), Trondheim, Norway. She received a first-class honours degree from the University of Glasgow, Scotland in 1991 and her PhD in 1998 from NTNU, Norway. She has chaired the complex, reliable and adaptive systems lab (CRAB lab) at NTNU for around 25 years. She has supervised/co-supervised
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A Self-Learning Framework for Large-Scale Conversational AI Systems IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Xiaohu Liu, Chenlei Guo, Benjamin Yao, Ruhi Sarikaya
In the last decade, conversational artificial intelligence (AI) systems have been widely employed to address people’s real-life needs across various different environments and settings. At the same time, users’ expectations of these systems have been on the rise as they expect more contextual and personalized interactions with continuous learning systems, akin to their expectation in human-human interactions
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Redefining Efficiency: The Rise of AI/CI-Assisted Innovations [Editor's Remarks] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Chuan-Kang Ting
In sci-fi novels and movies, AI is often portrayed as a symbol representing either an ultimate adversary threatening human existence or a focal point provoking ethical and societal debate. While public perception of AI oscillates between recognizing its widespread benefits and fearing the chaos it could unleash upon humanity, it is undeniable that AI and CI technologies are increasingly integrating
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FairerML: An Extensible Platform for Analysing, Visualising, and Mitigating Biases in Machine Learning [Application Notes] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Bo Yuan, Shenhao Gui, Qingquan Zhang, Ziqi Wang, Junyi Wen, Bifei Mao, Jialin Liu, Xin Yao
Given the growing concerns about bias in machine learning, dozens of metrics have been proposed to measure the fairness of machine learning. Several platforms have also been developed to compute and illustrate fairness metrics on platform-provided data. However, most platforms do not provide a user-friendly interface for users to upload and evaluate their own data or machine learning models. Moreover
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Share Your Preprint Research with the World! IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05
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Call for Papers for Journal Special Issues IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05
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Conference Calendar [Conference Calendar] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Leandro Lei Minku, Liyan Song
The 2nd International Conference on Cyber-energy Systems and Intelligent Energies (ICCSIE 2024)
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Hierarchical Bipartite Graph Convolutional Network for Recommendation IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Yi-Wei Cheng, Zhiqiang Zhong, Jun Pang, Cheng-Te Li
Graph Neural Networks (GNNs) have emerged as a dominant paradigm in machine learning for graphs, and recently developed Recommendation System (RecSys) models have significantly benefited from them. However, recent research has highlighted a limitation in classical GNNs, revealing that their message-passing mechanism is inherently flat, making it unable to capture hierarchical semantics within the graph
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Genetic Programming and Reinforcement Learning on Learning Heuristics for Dynamic Scheduling: A Preliminary Comparison IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Meng Xu, Yi Mei, Fangfang Zhang, Mengjie Zhang
Scheduling heuristics are commonly used to solve dynamic scheduling problems in real-world applications. However, designing effective heuristics can be time-consuming and often leads to suboptimal performance. Genetic programming has been widely used to automatically learn scheduling heuristics. In recent years, reinforcement learning has also gained attention in this field. Understanding their strengths
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AI for Materials Design and Discovery Using Atomistic Scale Information [Industrial and Governmental Activities] IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-04-05 Massimiliano Lupo Pasini
The design and discovery of materials with desired functional properties is pivotal to the scientific mission of the United States Department of Energy (US-DOE) [1], which includes within its portfolio several important applications for the national economy and security. These applications range from: renewable energy (e.g., solar cells, organic photovoltaics, and organic light-emitting diodes), energy
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Call for Papers for Journal Special Issues IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-01-08
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Call for Participation: IEEE World Congress on Computational Intelligence IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-01-08
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IEEE Computational Intelligence Society Publications IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-01-08
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Share Your Preprint Research with the World! IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-01-08
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2024 IEEE Conference on Artificial Intelligence IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-01-08
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IEEE Connects You to a Universe of Information! IEEE Comput. Intell. Mag. (IF 10.3) Pub Date : 2024-01-08
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