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Call for Participation: IEEE World Congress on Computational Intelligence IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08
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IEEE Computational Intelligence Society Publications IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08
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Share Your Preprint Research with the World! IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08
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2024 IEEE Conference on Artificial Intelligence IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08
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IEEE Connects You to a Universe of Information! IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08
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CIS-ing in an Uncertain World [President's Message] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Yaochu Jin
I am deeply honored to serve as the President of the IEEE Computational Intelligence Society (CIS) for 2024-2025. I had never imagined that I would become the President of our society when I joined IEEE at the 1998 World Congress on Computational Intelligence. I would take this opportunity to thank Bernadette Bouchon-Meunier, chair of the nomination committee and her colleagues, for their trust. I
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IEEE CIS VP-Conferences Vision Statement [Society Briefs] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Leandro L. Minku
It is a great honor and a privilege for me to serve as the Vice President for Conferences of the IEEE Computational Intelligence Society (CIS). Conferences are one of the main avenues for Computational Intelligence (CI) researchers to interact with each other and exchange ideas for the advancement of the field. CIS has a long history of providing high-quality conferences on various CI topics for our
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IEEE CIS VP-Technical Activities Vision Statement [Society Briefs] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Christian Wagner
It is a real pleasure and privilege to have been elected to and to serve as Vice President for Technical Activities of the IEEE Computational Intelligence Society (CIS) for 2024 and 2025. CIS is a vibrant home for individuals from all walks of life who are passionate about the theory, design, application, and development of a broad range of artificially intelligent systems. Just as the technology,
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2024 IEEE CIS Awards [Society Briefs] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Chin-Teng Lin
He is author of the books “Artificial Neural Networks for Modelling and Control of Non-linear Systems” (Springer) and “Least Squares Support Vector Machines” (World Scientific), co-author of the book “Cellular Neural Networks, Multi-Scroll Chaos and Synchronization” (World Scientific) and editor of the books “Nonlinear Modeling: Advanced Black-Box Techniques” (Springer), “Advances in Learning Theory:
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Acknowledging Volunteers Associated With 2023 IEEE CIS Conference Management [Society Briefs] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Marley Velasco, Steven Corns
The IEEE Computational Society (CIS) offers many financially-sponsored conferences each year. All of these depend on the hard work and effort of volunteers who propose and then organize these events in the pursuit of a healthy exchange of information and improvement in the application and theory of computational intelligence approaches. The last few years in particular have been a challenging time
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Guest Editorial: AI-eXplained (Part II) [Guest Editorial] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Pau-Choo Chung, Alexander Dockhorn, Jen-Wei Huang
Thanks to the many submissions we have received, we can present this second part of our special issue on “AI-eXplained.” In here, we continue our mission to demystify the intricate world of artificial intelligence and make it accessible to a broader audience. As AI continues to evolve and integrate into various aspects of our lives, it becomes increasingly important to bridge the gap between experts
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CIS: Connect It Strong! [Editor's Remarks] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Chuan-Kang Ting
The beginning of a year is a good timing to conclude on what memorable moments have happened in the preceding year. Last summer, I was invited to give talks at the 2023 IEEE CIS Summer School and Summit Forum held at the Southern University of Science and Technology (SUSTech) in Shenzhen, China. Several IEEE CIS officers, Editors-in-Chief, and I gathered to introduce CI techniques and their advancements
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AI in Industrial IoT Cybersecurity [Industrial and Governmental Activities] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Kai Goebel, Shantanu Rane
Ai's role within the domain of Industrial IoT (IIoT) is somewhat obscured by other limelight-stealing feats of AI, such as the creation of convincing deep fakes featuring politicians or celebrities. However, the critical importance of IIoT in domains like consumer goods manufacturing, healthcare, power generation, and transportation mandates a closer examination of the new capabilities and pitfalls
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Breaking Boundaries Initiative: Workshop on Industry-Academia Collaboration [Technical Activities] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Marcin Pietrasik, Anna Wilbik, Paul Grefen, Christian Wagner, Luis Magdalena
Reports on the activities and discussions that were part of the Breaking Boundaries: Industry-Academia Workshop that took place on the 27th and 28th of June 2023 at Maastricht University in The Netherlands.
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The IEEE XES Standard for Process Mining: Experiences, Adoption, and Revision [Society Briefs] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Moe T. Wynn, Wil van der Aalst, Eric Verbeek, Bruno Di Stefano
The IEEE Standards Association (SA) officially published the XES Standard as IEEE Std 1849-2016: IEEE Standard for eXtensible Event Stream (XES) for Achieving Interoperability in Event Logs and Event Streams on 11 November 2016. This standard has been sponsored by the IEEE Computational Intelligence Society (CIS) Standards Committee. Through the XES Standard, event data can be transported from the
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CIS Publication Spotlight [Publication Spotlight] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Yongduan Song, Dongrui Wu, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yiu-ming Cheung
“Large-scale multiobjective optimization problems (LSMOPs) are characterized as optimization problems involving hundreds or even thousands of decision variables and multiple conflicting objectives. To solve LSMOPs, some algorithms designed a variety of strategies to track Pareto-optimal solutions (POSs) by assuming that the distribution of POSs follows a low-dimensional manifold. However, traditional
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Forward Composition Propagation for Explainable Neural Reasoning IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Isel Grau, Gonzalo Nápoles, Marilyn Bello, Yamisleydi Salgueiro, Agnieszka Jastrzebska
This paper proposes an algorithm called Forward Composition Propagation (FCP) to explain the predictions of feed-forward neural networks operating on structured classification problems. In the proposed FCP algorithm, each neuron is described by a composition vector indicating the role of each problem feature in that neuron. Composition vectors are initialized using a given input instance and subsequently
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Dual Sparse Structured Subspaces and Graph Regularisation for Particle Swarm Optimisation-Based Multi-Label Feature Selection IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Kaan Demir, Bach Hoai Nguyen, Bing Xue, Mengjie Zhang
Many real-world classification problems are becoming multi-label in nature, i.e., multiple class labels are assigned to an instance simultaneously. Multi-label classification is a challenging problem due to the involvement of three forms of interactions, i.e., feature-to-feature, feature-to-label, and label-to-label interactions. What further complicates the problem is that not all features are useful
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SPAIC: A Spike-Based Artificial Intelligence Computing Framework IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Chaofei Hong, Mengwen Yuan, Mengxiao Zhang, Xiao Wang, Chengjun Zhang, Jiaxin Wang, Gang Pan, Huajin Tang
Neuromorphic computing is an emerging research field that aims to develop new intelligent systems by integrating theories and technologies from multiple disciplines, such as neuroscience, deep learning and microelectronics. Various software frameworks have been developed for related fields, but an efficient framework dedicated to spike-based computing models and algorithms is lacking. In this work
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When Evolutionary Computation Meets Privacy IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Bowen Zhao, Wei-Neng Chen, Xiaoguo Li, Ximeng Liu, Qingqi Pei, Jun Zhang
Recently, evolutionary computation (EC) has experienced significant advancements due to the integration of machine learning, distributed computing, and big data technologies. These developments have led to new research avenues in EC, such as distributed EC and surrogate-assisted EC. While these advancements have greatly enhanced the performance and applicability of EC, they have also raised concerns
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Interactive Augmentations, Features, and Parameters for Contrastive Learning [AI-eXplained] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Yu-Ting Chen, Chien-Yu Chiou, Chun-Rong Huang
Recently, contrastive learning has shown its effectiveness in self-supervised learning by training features of augmentations of input images based on the contrastive loss. This paper aims to introduce contrastive learning and discuss the effects of augmentations, features, and parameters of contrastive learning. Interactive figures are developed to demonstrate the effective schemes proposed in contrastive
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How to Build Self-Explaining Fuzzy Systems: From Interpretability to Explainability [AI-eXplained] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Ilia Stepin, Muhammad Suffian, Alejandro Catala, Jose M. Alonso-Moral
Fuzzy systems are known to provide not only accurate but also interpretable predictions. However, their explainability may be undermined if non-semantically grounded linguistic terms are used. Additional non-trivial challenges would arise if a prediction were to be explained counterfactually, i.e., in terms of hypothetical, non-predicted outputs. In this paper, we explore how both factual and counterfactual
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An Interactive Approach to Build Fuzzy Color Spaces [AI-eXplained] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Míriam Mengíbar-Rodríguez, Jesús Chamorro-Martínez, James M. Keller
In this paper, the idea of a fuzzy color and a fuzzy color space is shown in an interactive way. It is proposed several interactive elements, where readers can understand the different steps to build them. Furthermore, these elements allow the user to test with his/her own images via the behavior of the fuzzy colors.
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Playing With Monte-Carlo Tree Search [AI-eXplained] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Yunlong Zhao, Chengpeng Hu, Jialin Liu
Recently, contrastive learning has shown its effectiveness in self-supervised learning by training features of augmentations of input images based on the contrastive loss. This paper aims to introduce contrastive learning and discuss the effects of augmentations, features, and parameters of contrastive learning. Interactive figures are developed to demonstrate the effective schemes proposed in contrastive
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Conference Calendar [Conference Calendar] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2024-01-08 Leandro L. Minku, Liyan Song
* Denotes a CIS-Sponsored Conference
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An Interaction Is Worth a Thousand Words [Editor's Remarks] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Chuan-Kang Ting
One year ago, CIM published the inaugural AI-eXplained (AI-X) immersive article on IEEE Xplore. It is thrilled to witness that our call for the new form of content representation has been responded to with tremendous passion and a surge of submissions. With great efforts, CIM offers a platform for delivering Al/CI concepts, designs, and applications via a vivid and innovative means of knowledge distribution
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Tempus Fugit! [President's Message] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Jim Keller
Wow, how time flies. It seems like only yesterday that I was writing my welcome column as your new President in the first issue of the 2022 CIM. Now it's time to hand over the reins to the 2024-2025 CIS President, Yaochu Jin. Yaochu will do a great job for CIS. It's been a great privilege and honor for me to serve as President, and really, it's been a blast. Both the field of computational intelligence
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Conference Report on the Inaugural 2023 IEEE Conference on Artificial Intelligence (IEEE CAI 2023) [Conference Reports] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Gary B. Fogel, Piero Bonissone
The inaugural 2023 IEEE Conference on Artificial Intelligence was held June 5-6 at the Hyatt Regency Santa Clara in California's Silicon Valley. This new event was several years in the making and included co-sponsorship by four IEEE societies including the IEEE Computational Intelligence Society (as lead organization for the first two years), IEEE Computer Society, IEEE Signal Processing Society, and
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Obituary for Michio Sugeno [In Memoriam] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Kazuo Tanaka
Recounts the career and contributions of Michio Sugeno.
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Surrogate-Assisted Many-Objective Optimization of Building Energy Management IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Qiqi Liu, Felix Lanfermann, Tobias Rodemann, Markus Olhofer, Yaochu Jin
Building energy management usually involves a number of objectives, such as investment costs, thermal comfort, system resilience, battery life, and many others. However, most existing studies merely consider optimizing less than three objectives since it becomes increasingly difficult as the number of objectives increases. In addition, the optimization of building energy management relies heavily on
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Learning Regularity for Evolutionary Multiobjective Search: A Generative Model-Based Approach IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Shuai Wang, Aimin Zhou, Guixu Zhang, Faming Fang
The prior domain knowledge, i.e., the regularity property of continuous multiobjective optimization problems (MOPs), could be learned to guide the search for evolutionary multiobjective optimization. This paper proposes a learning-to-guide strategy (LGS) for assisting the search for multiobjective optimization algorithms in dealing with MOPs. The main idea behind LGS is to capture the regularity via
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RoCaSH2: An Effective Route Clustering and Search Heuristic for Large-Scale Multi-Depot Capacitated Arc Routing Problem IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Yuzhou Zhang, Yi Mei, Haiqi Zhang, Qinghua Cai, Haifeng Wu
The Multi-Depot Capacitated Arc Routing Problem (MDCARP) is an important combinatorial optimization problem with wide applications in logistics. Large Scale MDCARP (LSMDCARP) often occurs in the real world, as the problem size (e.g., number of edges/tasks) is usually very large in practice. It is challenging to solve LSMDCARP due to the large search space and complex interactions among the depots and
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AI-Explained (Part I) [Guest Editorial] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Pau-Choo Chung, Alexander Dockhorn, Jen-Wei Huang
As we witness the remarkable progress of artificial intelligence (AI) over the last decade, its potential to address real-world complexities and revolutionize various fields has become evident. From image processing to natural language translation, AI solutions have accomplished significant milestones. However, the growing importance of AI in diverse domains has raised the need for making this complex
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Group Formation by Group Joining and Opinion Updates Via Multi-Agent Online Gradient Ascent [AI-eXplained] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Chuang-Chieh Lin, Chih-Chieh Hung, Chi-Jen Lu, Po-An Chen
This article aims to exemplify best-response dynamics and multi-agent online learning by group formation. This extended abstract provides a summary of the full paper in IEEE Computational Intelligence Magazine on the special issue AI-eXplained (AI-X). The full paper includes interactive components to facilitate interested readers to grasp the idea of pure-strategy Nash equilibria and how the system
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Monte Carlo and Temporal Difference Methods in Reinforcement Learning [AI-eXplained] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Isaac Han, Seungwon Oh, Hoyoun Jung, Insik Chung, Kyung-Joong Kim
Reinforcement learning (RL) is a subset of machine learning that allows intelligent agents to acquire the ability of executing desired actions through interactions with an environment. Its remarkable progress has achieved significant results in diverse domains, such as Go and StarCraft, and practical challenges like protein-folding. This short paper presents overviews of two common RL approaches: the
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Correspondence-Free Point Cloud Registration Via Feature Interaction and Dual Branch [Application Notes] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Yue Wu, Jiaming Liu, Yongzhe Yuan, Xidao Hu, Xiaolong Fan, Kunkun Tu, Maoguo Gong, Qiguang Miao, Wenping Ma
Point cloud registration, which effectively coincides the source and target point clouds, is generally implemented by geometric metrics or feature metrics. In terms of resistance to noise and outliers, feature-metric registration has less error than the traditional point-to-point corresponding geometric metric, and point cloud reconstruction can generate and reveal more potential information during
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Conference Calendar [Conference Calendar] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Marley Vellasco, Liyan Song
The 7th Asian Conference on Artificial Intelligence Technology (ACAIT 2023)
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CIS Publication Spotlight [Publication Spotlight] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Yongduan Song, Dongrui Wu, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yiu-Ming Cheung, Hussein Abbass
Presents summaries of recent books published in the area of computational intelligence.
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MAP-Elites for Genetic Programming-Based Ensemble Learning: An Interactive Approach [AI-eXplained] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-10-17 Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang
Evolutionary ensemble learning is an emerging research area, and designing an appropriate quality-diversity optimization algorithm to obtain a set of effective and complementary base learners is important. However, how to maintain such a set of learners remains an open issue. This paper proposes using cosine similarity-based dimensionality reduction methods to maintain a set of effective and complementary
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Takeaways From CI Leading Researchers [Editor's Remarks] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Chuan-Kang Ting
With the pandemic subsiding, academic activities are reviving rapidly around the world. In May 2023, I organized the AI Forum 2023 and had the honor to invite Yaochu Jin, Kay Chen Tan, and Yew Soon Ong to deliver keynote speeches about cutting-edge CI technologies and, in particular, to share their valuable research experience at the panel discussion. One thing these former Editors-in-Chief of IEEE
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Chat, Anyone? [President's Message] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Jim Keller
Let's talk about the elephant in the room. ChatGPT and other Large Language Models (LLM) along with their AI cousins focused on images, graphics, math, coding, and audio are dominating our world of generating reports and manuscripts. They can be immensely fun: I asked ChatGPT to write me song lyrics about fuzzy logic in various genres. I wasn't crazy about the folk song, but I really liked ChatGPT's
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Conference Report on 2022 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2022) [Conference Reports] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Ah-Hwee Tan, Dipti Srinivasan, Chunyan Miao
On behalf of the organizing committee, we are delighted to deliver this conference report for the 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022), which was held in Singapore from 4th to 7th December 2022. IEEE SSCI is an established flagship annual international series of symposia on computational intelligence (CI) sponsored by the IEEE Computational Intelligence Society (CIS)
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CIS Publication Spotlight [Publication Spotlight] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Yongduan Song, Dongrui Wu, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yiu-Ming Cheung, Hussein Abbass
A Survey on Evolutionary Neural Architecture Search, by Y. Liu, Y. Sun, B. Xue, M. Zhang, G. G. Yen, and K. C. Tan, IEEE Transactions on Neural Networks and Learning Systems, Vol. 34, No. 2, Feb. 2023, pp. 550–570.
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How Good is Neural Combinatorial Optimization? A Systematic Evaluation on the Traveling Salesman Problem IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Shengcai Liu, Yu Zhang, Ke Tang, Xin Yao
Traditional solvers for tackling combinatorial optimization (CO) problems are usually designed by human experts. Recently, there has been a surge of interest in utilizing deep learning, especially deep reinforcement learning, to automatically learn effective solvers for CO. The resultant new paradigm is termed neural combinatorial optimization (NCO). However, the advantages and disadvantages of NCO
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Jack and Masters of all Trades: One-Pass Learning Sets of Model Sets From Large Pre-Trained Models IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Han Xiang Choong, Yew-Soon Ong, Abhishek Gupta, Caishun Chen, Ray Lim
For deep learning, size is power. Massive neural nets trained on broad data for a spectrum of tasks are at the forefront of artificial intelligence. These large pre-trained models or “Jacks of All Trades” (JATs), when fine-tuned for downstream tasks, are gaining importance in driving deep learning advancements. However, environments with tight resource constraints, changing objectives and intentions
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A Multi-Factorial Evolutionary Algorithm With Asynchronous Optimization Processes for Solving the Robust Influence Maximization Problem IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Shuai Wang, Beichen Ding, Yaochu Jin
The complex network has attracted increasing attention and shown effectiveness in modeling multifarious systems. Focusing on selecting members with good spreading ability, the influence maximization problem is of great significance in network-based information diffusion tasks. Plenty of attention has been paid to simulating the diffusion process and choosing influential seeds. However, errors and attacks
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Multi-Magnification Attention Convolutional Neural Networks [AI-eXplained] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Chia-Wei Chao, Daniel Winden Hwang, Hung-Wen Tsai, Shih-Hsuan Lin, Wei-Li Chen, Chun-Rong Huang, Pau-Choo Chung
To apply convolutional neural networks (CNNs) on high-resolution images, a common approach is to split the input image into smaller patches. However, the field-of-view is restricted by the input size. To overcome the problem, a multi-magnification attention convolutional neural network (MMA-CNN) is proposed to analyze images based on both local and global features. Our approach focuses on identifying
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Contribution-Based Cooperative Co-Evolution With Adaptive Population Diversity for Large-Scale Global Optimization [Research Frontier] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Ming Yang, Jie Gao, Aimin Zhou, Changhe Li, Xin Yao
Cooperative co-evolution (CC) is an evolutionary algorithm that adopts the divide-and-conquer strategy to solve large-scale optimization problems. It is difficult for CC to specify a suitable subpopulation size to solve different subproblems. The population diversity may be insufficient to search for the global optimum during subpopulations’ evolution. In this paper, an adaptive method for enhancing
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A Macro-Micro Population-Based Co-Evolutionary Multi-Objective Algorithm for Community Detection in Complex Networks [Research Frontier] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Lei Zhang, Haipeng Yang, Shangshang Yang, Xingyi Zhang
Recently, multi-objective evolutionary algorithms (MOEAs) have shown promising performance in terms of community detection in complex networks. However, most studies have focused on designing different strategies to achieve good community detection performance based on a single population. Unlike these studies, this study proposes a macro-micro population-based co-evolutionary multi-objective algorithm
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Conference Calendar [Conference Calendar] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-07-19 Marley Vellasco, Liyan Song
* 2023 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2023)
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Reembracing the Physical World [Editor's Remarks] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-04-13 Chuan-Kang Ting
After attending numerous video conferences and missing IEEE WCCI 2022 in Padua due to the COVID-19 pandemic, I finally got to mingle with the IEEE SSCI 2022 and the A*STAR CFAR AI Symposium attendees in Singapore. Words could not express my sheer excitement for meeting with friends again “in person”. It was much more fun than staring at each other via individuals’ cold computer screens. And I must
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Midyear Musings [President's Message] IEEE Comput. Intell. Mag. (IF 9.0) Pub Date : 2023-04-13 Jim Keller
As this issue is published, 2023 is well underway. I don't have a set theme for this message – I will just ramble along for a while writing about accomplishments, on-going activities, and plans for the Computational Intelligence Society. Not so original, eh?