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  2025 (1)
Knowledge graph embedding based on embedding permutation and high-frequency feature fusion for link prediction. Yu, Q.; and Vargas, D. V. Neurocomputing, 633: 129743. 2025.
Knowledge graph embedding based on embedding permutation and high-frequency feature fusion for link prediction [link]Paper   doi   link   bibtex   2 downloads  
  2024 (8)
Improving robustness for vision transformer with a simple dynamic scanning augmentation. Kotyan, S.; and Vargas, D. V. Neurocomputing, 565: 127000. 2024.
Improving robustness for vision transformer with a simple dynamic scanning augmentation [link]Paper   doi   link   bibtex   2 downloads  
Robust Visual Reinforcement Learning by Prompt Tuning. Tran, T.; Than, K.; and Vargas, D. V. In Cho, M.; Laptev, I.; Tran, D.; Yao, A.; and Zha, H., editor(s), Computer Vision - ACCV 2024 - 17th Asian Conference on Computer Vision, Hanoi, Vietnam, December 8-12, 2024, Proceedings, Part IX, volume 15480, of Lecture Notes in Computer Science, pages 387–401, 2024. Springer
Robust Visual Reinforcement Learning by Prompt Tuning [link]Paper   doi   link   bibtex  
Extending Token Computation for LLM Reasoning. Li, B.; and Vargas, D. V. In Chen, X.; and Fang, J., editor(s), Proceedings of the 2024 8th International Conference on Computer Science and Artificial Intelligence, CSAI 2024, BeijingChina, December 6-8, 2024, pages 367–373, 2024. ACM
Extending Token Computation for LLM Reasoning [link]Paper   doi   link   bibtex  
EvoSeed: Unveiling the Threat on Deep Neural Networks with Real-World Illusions. Kotyan, S.; Mao, P.; and Vargas, D. V. CoRR, abs/2402.04699. 2024.
EvoSeed: Unveiling the Threat on Deep Neural Networks with Real-World Illusions [link]Paper   doi   link   bibtex  
Attention-Driven Reasoning: Unlocking the Potential of Large Language Models. Liao, B.; and Vargas, D. V. CoRR, abs/2403.14932. 2024.
Attention-Driven Reasoning: Unlocking the Potential of Large Language Models [link]Paper   doi   link   bibtex  
Adapting to Covariate Shift in Real-time by Encoding Trees with Motion Equations. Foong, T. Y.; Zhang, H.; Yuan, M. P.; and Vargas, D. V. CoRR, abs/2404.05168. 2024.
Adapting to Covariate Shift in Real-time by Encoding Trees with Motion Equations [link]Paper   doi   link   bibtex  
Beyond KV Caching: Shared Attention for Efficient LLMs. Liao, B.; and Vargas, D. V. CoRR, abs/2407.12866. 2024.
Beyond KV Caching: Shared Attention for Efficient LLMs [link]Paper   doi   link   bibtex  
Linking Robustness and Generalization: A k* Distribution Analysis of Concept Clustering in Latent Space for Vision Models. Kotyan, S.; Chen, P.; and Vargas, D. V. CoRR, abs/2408.09065. 2024.
Linking Robustness and Generalization: A k* Distribution Analysis of Concept Clustering in Latent Space for Vision Models [link]Paper   doi   link   bibtex  
  2023 (14)
A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning. Zhang, H.; and Vargas, D. V. IEEE Access, 11: 81033–81070. 2023.
A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning [link]Paper   doi   link   bibtex   6 downloads  
Magnum: Tackling high-dimensional structures with self-organization. Mao, P.; Tham, Y.; Zhang, H.; and Vargas, D. V. Neurocomputing, 550: 126508. 2023.
Magnum: Tackling high-dimensional structures with self-organization [link]Paper   doi   link   bibtex   2 downloads  
Generating oscillation activity with Echo State Network to mimic the behaviour of a simple central pattern generator. Foong, T. Y.; and Vargas, D. V. In Goldwater, M. B.; Anggoro, F. K.; Hayes, B. K.; and Ong, D. C., editor(s), Proceedings of the 45th Annual Meeting of the Cognitive Science Society, CogSci 2023, Sydney, NSW, Australia, July 26-29, 2023, 2023. cognitivesciencesociety.org
Generating oscillation activity with Echo State Network to mimic the behaviour of a simple central pattern generator [link]Paper   link   bibtex  
Curious-II: A Multi/Many-Objective Optimization Algorithm with Subpopulations based on Multi-novelty Search. Jiang, Y.; and Vargas, D. V. In Silva, S.; and Paquete, L., editor(s), Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023, pages 375–378, 2023. ACM
Curious-II: A Multi/Many-Objective Optimization Algorithm with Subpopulations based on Multi-novelty Search [link]Paper   doi   link   bibtex   1 download  
Dynamical Equations With Bottom-up Self-Organizing Properties Learn Accurate Dynamical Hierarchies Without Any Loss Function. Vargas, D. V.; Foong, T. Y.; and Zhang, H. CoRR, abs/2302.02140. 2023.
Dynamical Equations With Bottom-up Self-Organizing Properties Learn Accurate Dynamical Hierarchies Without Any Loss Function [link]Paper   doi   link   bibtex   2 downloads  
Generating Oscillation Activity with Echo State Network to Mimic the Behavior of a Simple Central Pattern Generator. Foong, T. Y.; and Vargas, D. V. CoRR, abs/2306.10927. 2023.
Generating Oscillation Activity with Echo State Network to Mimic the Behavior of a Simple Central Pattern Generator [link]Paper   doi   link   bibtex   1 download  
A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning. Zhang, H.; and Vargas, D. V. CoRR, abs/2307.15092. 2023.
A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning [link]Paper   doi   link   bibtex   6 downloads  
Symmetrical SyncMap for Imbalanced General Chunking Problems. Zhang, H.; and Vargas, D. V. CoRR, abs/2310.10045. 2023.
Symmetrical SyncMap for Imbalanced General Chunking Problems [link]Paper   doi   link   bibtex   2 downloads  
Improving Robustness for Vision Transformer with a Simple Dynamic Scanning Augmentation. Kotyan, S.; and Vargas, D. V. CoRR, abs/2311.00441. 2023.
Improving Robustness for Vision Transformer with a Simple Dynamic Scanning Augmentation [link]Paper   doi   link   bibtex  
Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning. Kotyan, S.; and Vargas, D. V. CoRR, abs/2311.07928. 2023.
Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning [link]Paper   doi   link   bibtex  
Towards Improving Robustness Against Common Corruptions using Mixture of Class Specific Experts. Kotyan, S.; and Vargas, D. V. CoRR, abs/2311.10177. 2023.
Towards Improving Robustness Against Common Corruptions using Mixture of Class Specific Experts [link]Paper   doi   link   bibtex  
The Challenges of Image Generation Models in Generating Multi-Component Images. Foong, T. Y.; Kotyan, S.; Mao, P.; and Vargas, D. V. CoRR, abs/2311.13620. 2023.
The Challenges of Image Generation Models in Generating Multi-Component Images [link]Paper   doi   link   bibtex  
k* Distribution: Evaluating the Latent Space of Deep Neural Networks using Local Neighborhood Analysis. Kotyan, S.; Ueda, T.; and Vargas, D. V. CoRR, abs/2312.04024. 2023.
k* Distribution: Evaluating the Latent Space of Deep Neural Networks using Local Neighborhood Analysis [link]Paper   doi   link   bibtex  
Synthetic Shifts to Initial Seed Vector Exposes the Brittle Nature of Latent-Based Diffusion Models. Mao, P.; Kotyan, S.; Foong, T. Y.; and Vargas, D. V. CoRR, abs/2312.11473. 2023.
Synthetic Shifts to Initial Seed Vector Exposes the Brittle Nature of Latent-Based Diffusion Models [link]Paper   doi   link   bibtex  
  2022 (3)
Understanding SyncMap's Dynamics and Its Self-organization Properties: A Space-time Analysis. Zhang, H.; and Vargas, D. V. In Proceedings of the 5th Artificial Intelligence and Cloud Computing Conference, AICCC 2022, Osaka, Japan, December 17-19, 2022, pages 14–20, 2022. ACM
Understanding SyncMap's Dynamics and Its Self-organization Properties: A Space-time Analysis [link]Paper   doi   link   bibtex  
Understanding SyncMap: Analyzing the components of Its Dynamical Equation. Foong, T. Y.; and Vargas, D. V. In Proceedings of the 5th Artificial Intelligence and Cloud Computing Conference, AICCC 2022, Osaka, Japan, December 17-19, 2022, pages 246–254, 2022. ACM
Understanding SyncMap: Analyzing the components of Its Dynamical Equation [link]Paper   doi   link   bibtex  
Image Generation from Text and Segmentation. Osugi, M.; and Vargas, D. V. In 2022 Tenth International Symposium on Computing and Networking, CANDAR 2022 - Workshops, Himeji, Japan, November 21-24, 2022, pages 206–211, 2022. IEEE
Image Generation from Text and Segmentation [link]Paper   doi   link   bibtex   6 downloads  
  2021 (8)
Continual General Chunking Problem and SyncMap. Vargas, D. V.; and Asabuki, T. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, pages 10006–10014, 2021. AAAI Press
Continual General Chunking Problem and SyncMap [link]Paper   doi   link   bibtex  
Towards Learning Hierarchical Structures with SyncMap. Foong, T. Y.; and Vargas, D. V. In 5th IEEE International Conference on Cybernetics, CYBCONF 2021, Sendai, Japan, June 8-10, 2021, pages 7–11, 2021. IEEE
Towards Learning Hierarchical Structures with SyncMap [link]Paper   doi   link   bibtex  
Parameter Optimization via CMA-ES for Implementation in the Active Control of Magnetic Pillar Arrays. Gaysornkaew, S.; Vargas, D. V.; and Tsumori, F. In 5th IEEE International Conference on Cybernetics, CYBCONF 2021, Sendai, Japan, June 8-10, 2021, pages 61–66, 2021. IEEE
Parameter Optimization via CMA-ES for Implementation in the Active Control of Magnetic Pillar Arrays [link]Paper   doi   link   bibtex  
Preliminary Results for Subpopulation Algorithm Based on Novelty (SAN) Compared with the State of the Art. Jiang, Y.; and Vargas, D. V. In 5th IEEE International Conference on Cybernetics, CYBCONF 2021, Sendai, Japan, June 8-10, 2021, pages 67–72, 2021. IEEE
Preliminary Results for Subpopulation Algorithm Based on Novelty (SAN) Compared with the State of the Art [link]Paper   doi   link   bibtex  
Towards Understanding The Space of Unrobust Features of Neural Networks. Liao, B.; Kanzaki, T.; and Vargas, D. V. In 5th IEEE International Conference on Cybernetics, CYBCONF 2021, Sendai, Japan, June 8-10, 2021, pages 91–94, 2021. IEEE
Towards Understanding The Space of Unrobust Features of Neural Networks [link]Paper   doi   link   bibtex  
Deep Neural Network Loses Attention to Adversarial Images. Kotyan, S.; and Vargas, D. V. In Espinoza, H.; McDermid, J. A.; Huang, X.; Castillo-Effen, M.; Chen, X. C.; Hernández-Orallo, J.; hÉigeartaigh , S. Ó; Mallah, R.; and Pedroza, G., editor(s), Proceedings of the Workshop on Artificial Intelligence Safety 2021 co-located with the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI 2021), Virtual, August, 2021, volume 2916, of CEUR Workshop Proceedings, 2021. CEUR-WS.org
Deep Neural Network Loses Attention to Adversarial Images [pdf]Paper   link   bibtex   1 download  
Towards Evaluating the Representation Learned by Variational AutoEncoders. Ueda, T.; and Vargas, D. V. In 60th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2021, Tokyo, Japan, September 8-10, 2021, pages 591–594, 2021. IEEE
Towards Evaluating the Representation Learned by Variational AutoEncoders [link]Paper   link   bibtex  
Deep neural network loses attention to adversarial images. Kotyan, S.; and Vargas, D. V. CoRR, abs/2106.05657. 2021.
Deep neural network loses attention to adversarial images [link]Paper   link   bibtex   1 download  
  2020 (8)
Towards improvement of SUNA in multiplexers with preliminary results of simple logic gate neuron variation. Ta, A. D.; and Vargas, D. V. In Coello, C. A. C., editor(s), GECCO '20: Genetic and Evolutionary Computation Conference, Companion Volume, Cancún, Mexico, July 8-12, 2020, pages 53–54, 2020. ACM
Towards improvement of SUNA in multiplexers with preliminary results of simple logic gate neuron variation [link]Paper   doi   link   bibtex  
Towards evolving robust neural architectures to defend from adversarial attacks. Kotyan, S.; and Vargas, D. V. In Coello, C. A. C., editor(s), GECCO '20: Genetic and Evolutionary Computation Conference, Companion Volume, Cancún, Mexico, July 8-12, 2020, pages 135–136, 2020. ACM
Towards evolving robust neural architectures to defend from adversarial attacks [link]Paper   doi   link   bibtex  
Preliminary study of applied binary neural networks for neural cryptography. Tenorio, R. H. V.; Sham, C.; and Vargas, D. V. In Coello, C. A. C., editor(s), GECCO '20: Genetic and Evolutionary Computation Conference, Companion Volume, Cancún, Mexico, July 8-12, 2020, pages 291–292, 2020. ACM
Preliminary study of applied binary neural networks for neural cryptography [link]Paper   doi   link   bibtex  
Evolving Robust Neural Architectures to Defend from Adversarial Attacks. Kotyan, S.; and Vargas, D. V. In Espinoza, H.; McDermid, J. A.; Huang, X.; Castillo-Effen, M.; Chen, X. C.; Hernández-Orallo, J.; hÉigeartaigh , S. Ó; and Mallah, R., editor(s), Proceedings of the Workshop on Artificial Intelligence Safety 2020 co-located with the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020), Yokohama, Japan, January, 2021, volume 2640, of CEUR Workshop Proceedings, 2020. CEUR-WS.org
Evolving Robust Neural Architectures to Defend from Adversarial Attacks [pdf]Paper   link   bibtex  
Understanding the One Pixel Attack: Propagation Maps and Locality Analysis. Vargas, D. V.; and Su, J. In Espinoza, H.; McDermid, J. A.; Huang, X.; Castillo-Effen, M.; Chen, X. C.; Hernández-Orallo, J.; hÉigeartaigh , S. Ó; and Mallah, R., editor(s), Proceedings of the Workshop on Artificial Intelligence Safety 2020 co-located with the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020), Yokohama, Japan, January, 2021, volume 2640, of CEUR Workshop Proceedings, 2020. CEUR-WS.org
Understanding the One Pixel Attack: Propagation Maps and Locality Analysis [pdf]Paper   link   bibtex  
One-Pixel Attack: Understanding and Improving Deep Neural Networks with Evolutionary Computation. Vargas, D. V. In Iba, H.; and Noman, N., editor(s), Deep Neural Evolution - Deep Learning with Evolutionary Computation, of Natural Computing Series, pages 401–430. Springer, 2020.
One-Pixel Attack: Understanding and Improving Deep Neural Networks with Evolutionary Computation [link]Paper   doi   link   bibtex  
Continual General Chunking Problem and SyncMap. Vargas, D. V.; and Asabuki, T. CoRR, abs/2006.07853. 2020.
Continual General Chunking Problem and SyncMap [link]Paper   link   bibtex   1 download  
Perceptual Deep Neural Networks: Adversarial Robustness through Input Recreation. Vargas, D. V.; Liao, B.; and Kanzaki, T. CoRR, abs/2009.01110. 2020.
Perceptual Deep Neural Networks: Adversarial Robustness through Input Recreation [link]Paper   link   bibtex  
  2019 (17)
Attacking convolutional neural network using differential evolution. Su, J.; Vargas, D. V.; and Sakurai, K. IPSJ Trans. Comput. Vis. Appl., 11: 1. 2019.
Attacking convolutional neural network using differential evolution [link]Paper   doi   link   bibtex  
One Pixel Attack for Fooling Deep Neural Networks. Su, J.; Vargas, D. V.; and Sakurai, K. IEEE Trans. Evol. Comput., 23(5): 828–841. 2019.
One Pixel Attack for Fooling Deep Neural Networks [link]Paper   doi   link   bibtex  
Universal Rules for Fooling Deep Neural Networks based Text Classification. Li, D.; Vargas, D. V.; and Sakurai, K. In IEEE Congress on Evolutionary Computation, CEC 2019, Wellington, New Zealand, June 10-13, 2019, pages 2221–2228, 2019. IEEE
Universal Rules for Fooling Deep Neural Networks based Text Classification [link]Paper   doi   link   bibtex  
Towards solving neural networks with optimization trajectory search. Parsenadze, L. T.; Vargas, D. V.; and Fujita, T. In López-Ibáñez, M.; Auger, A.; and Stützle, T., editor(s), Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2019, Prague, Czech Republic, July 13-17, 2019, pages 75–76, 2019. ACM
Towards solving neural networks with optimization trajectory search [link]Paper   doi   link   bibtex  
Batch tournament selection for genetic programming: the quality of lexicase, the speed of tournament. de Melo, V. V.; Vargas, D. V.; and Banzhaf, W. In Auger, A.; and Stützle, T., editor(s), Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2019, Prague, Czech Republic, July 13-17, 2019, pages 994–1002, 2019. ACM
Batch tournament selection for genetic programming: the quality of lexicase, the speed of tournament [link]Paper   doi   link   bibtex  
Frame Difference Generative Adversarial Networks: Clearer Contour Video Generating. Qiu, R.; Vargas, D. V.; and Sakurai, K. In Seventh International Symposium on Computing and Networking Workshops, CANDAR 2019 Workshops, Nagasaki, Japan, November 26-29, 2019, pages 169–175, 2019. IEEE
Frame Difference Generative Adversarial Networks: Clearer Contour Video Generating [link]Paper   doi   link   bibtex  
Self Training Autonomous Driving Agent. Kotyan, S.; Vargas, D. V.; and Udutalapally, V. In 58th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2019, Hiroshima, Japan, September 10-13, 2019, pages 1456–1461, 2019. IEEE
Self Training Autonomous Driving Agent [link]Paper   doi   link   bibtex   4 downloads  
General Subpopulation Framework and Taming the Conflict Inside Populations. Vargas, D. V.; Murata, J.; Takano, H.; and Delbem, A. C. B. CoRR, abs/1901.00266. 2019.
General Subpopulation Framework and Taming the Conflict Inside Populations [link]Paper   link   bibtex   1 download  
Universal Rules for Fooling Deep Neural Networks based Text Classification. Li, D.; Vargas, D. V.; and Sakurai, K. CoRR, abs/1901.07132. 2019.
Universal Rules for Fooling Deep Neural Networks based Text Classification [link]Paper   link   bibtex  
Understanding the One-Pixel Attack: Propagation Maps and Locality Analysis. Vargas, D. V.; and Su, J. CoRR, abs/1902.02947. 2019.
Understanding the One-Pixel Attack: Propagation Maps and Locality Analysis [link]Paper   link   bibtex  
Spectrum-Diverse Neuroevolution with Unified Neural Models. Vargas, D. V.; and Murata, J. CoRR, abs/1902.06703. 2019.
Spectrum-Diverse Neuroevolution with Unified Neural Models [link]Paper   link   bibtex  
Tackling Unit Commitment and Load Dispatch Problems Considering All Constraints with Evolutionary Computation. Vargas, D. V.; Murata, J.; and Takano, H. CoRR, abs/1903.09304. 2019.
Tackling Unit Commitment and Load Dispatch Problems Considering All Constraints with Evolutionary Computation [link]Paper   link   bibtex  
Batch Tournament Selection for Genetic Programming. de Melo, V. V.; Vargas, D. V.; and Banzhaf, W. CoRR, abs/1904.08658. 2019.
Batch Tournament Selection for Genetic Programming [link]Paper   link   bibtex  
Self Training Autonomous Driving Agent. Kotyan, S.; Vargas, D. V.; and Udutalapally, V. CoRR, abs/1904.12738. 2019.
Self Training Autonomous Driving Agent [link]Paper   link   bibtex   4 downloads  
Model Agnostic Dual Quality Assessment for Adversarial Machine Learning and an Analysis of Current Neural Networks and Defenses. Vargas, D. V.; and Kotyan, S. CoRR, abs/1906.06026. 2019.
Model Agnostic Dual Quality Assessment for Adversarial Machine Learning and an Analysis of Current Neural Networks and Defenses [link]Paper   link   bibtex  
Uncovering Why Deep Neural Networks Lack Robustness: Representation Metrics that Link to Adversarial Attacks. Vargas, D. V.; Kotyan, S.; and Matsuki, M. CoRR, abs/1906.06627. 2019.
Uncovering Why Deep Neural Networks Lack Robustness: Representation Metrics that Link to Adversarial Attacks [link]Paper   link   bibtex  
Evolving Robust Neural Architectures to Defend from Adversarial Attacks. Vargas, D. V.; and Kotyan, S. CoRR, abs/1906.11667. 2019.
Evolving Robust Neural Architectures to Defend from Adversarial Attacks [link]Paper   link   bibtex  
  2018 (13)
Lightweight Classification of IoT Malware Based on Image Recognition. Su, J.; Vargas, D. V.; Prasad, S.; Sgandurra, D.; Feng, Y.; and Sakurai, K. In Reisman, S.; Ahamed, S. I.; Demartini, C.; Conte, T. M.; Liu, L.; Claycomb, W. R.; Nakamura, M.; Tovar, E.; Cimato, S.; Lung, C.; Takakura, H.; Yang, J.; Akiyama, T.; Zhang, Z.; and Hasan, M. K., editor(s), 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018, Tokyo, Japan, 23-27 July 2018, Volume 2, pages 664–669, 2018. IEEE Computer Society
Lightweight Classification of IoT Malware Based on Image Recognition [link]Paper   doi   link   bibtex  
Introducing learning classifier systems: rules that capture complexity. Urbanowicz, R. J.; and Vargas, D. V. In Aguirre, H. E.; and Takadama, K., editor(s), Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2018, Kyoto, Japan, July 15-19, 2018, pages 619–648, 2018. ACM
Introducing learning classifier systems: rules that capture complexity [link]Paper   doi   link   bibtex  
Evolutionary reinforcement learning: general models and adaptation. Vargas, D. V. In Aguirre, H. E.; and Takadama, K., editor(s), Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2018, Kyoto, Japan, July 15-19, 2018, pages 1017–1038, 2018. ACM
Evolutionary reinforcement learning: general models and adaptation [link]Paper   doi   link   bibtex  
Empirical Evaluation on Robustness of Deep Convolutional Neural Networks Activation Functions Against Adversarial Perturbation. Su, J.; Vargas, D. V.; and Sakurai, K. In Sixth International Symposium on Computing and Networking, CANDAR Workshops 2018, Takayama, Japan, November 27-30, 2018, pages 223–227, 2018. IEEE Computer Society
Empirical Evaluation on Robustness of Deep Convolutional Neural Networks Activation Functions Against Adversarial Perturbation [link]Paper   doi   link   bibtex  
Neural Cryptography Based on the Topology Evolving Neural Networks. Zhu, Y.; Vargas, D. V.; and Sakurai, K. In Sixth International Symposium on Computing and Networking, CANDAR Workshops 2018, Takayama, Japan, November 27-30, 2018, pages 472–478, 2018. IEEE Computer Society
Neural Cryptography Based on the Topology Evolving Neural Networks [link]Paper   doi   link   bibtex  
Tracing MIRAI Malware in Networked System. Xu, Y.; Koide, H.; Vargas, D. V.; and Sakurai, K. In Sixth International Symposium on Computing and Networking, CANDAR Workshops 2018, Takayama, Japan, November 27-30, 2018, pages 534–538, 2018. IEEE Computer Society
Tracing MIRAI Malware in Networked System [link]Paper   doi   link   bibtex  
A New Design for Evaluating Moving Target Defense System. Oo, W. K. K.; Koide, H.; Vargas, D. V.; and Sakurai, K. In Sixth International Symposium on Computing and Networking, CANDAR Workshops 2018, Takayama, Japan, November 27-30, 2018, pages 561–563, 2018. IEEE Computer Society
A New Design for Evaluating Moving Target Defense System [link]Paper   doi   link   bibtex   1 download  
Lightweight Classification of IoT Malware based on Image Recognition. Su, J.; Vargas, D. V.; Prasad, S.; Sgandurra, D.; Feng, Y.; and Sakurai, K. CoRR, abs/1802.03714. 2018.
Lightweight Classification of IoT Malware based on Image Recognition [link]Paper   link   bibtex  
Attacking Convolutional Neural Network using Differential Evolution. Su, J.; Vargas, D. V.; and Sakurai, K. CoRR, abs/1804.07062. 2018.
Attacking Convolutional Neural Network using Differential Evolution [link]Paper   link   bibtex  
Novelty-organizing team of classifiers in noisy and dynamic environments. Vargas, D. V.; Takano, H.; and Murata, J. CoRR, abs/1809.07098. 2018.
Novelty-organizing team of classifiers in noisy and dynamic environments [link]Paper   link   bibtex  
Contingency Training. Vargas, D. V.; Takano, H.; and Murata, J. CoRR, abs/1811.08214. 2018.
Contingency Training [link]Paper   link   bibtex  
Self Organizing Classifiers: First Steps in Structured Evolutionary Machine Learning. Vargas, D. V.; Takano, H.; and Murata, J. CoRR, abs/1811.08225. 2018.
Self Organizing Classifiers: First Steps in Structured Evolutionary Machine Learning [link]Paper   link   bibtex  
Self Organizing Classifiers and Niched Fitness. Vargas, D. V.; Takano, H.; and Murata, J. CoRR, abs/1811.08226. 2018.
Self Organizing Classifiers and Niched Fitness [link]Paper   link   bibtex   2 downloads  
  2017 (4)
Spectrum-Diverse Neuroevolution With Unified Neural Models. Vargas, D. V.; and Murata, J. IEEE Trans. Neural Networks Learn. Syst., 28(8): 1759–1773. 2017.
Spectrum-Diverse Neuroevolution With Unified Neural Models [link]Paper   doi   link   bibtex  
Effectively Protect Your Privacy: Enabling Flexible Privacy Control on Web Tracking. Yu, S.; Vargas, D. V.; and Sakurai, K. In Fifth International Symposium on Computing and Networking, CANDAR 2017, Aomori, Japan, November 19-22, 2017, pages 533–536, 2017. IEEE Computer Society
Effectively Protect Your Privacy: Enabling Flexible Privacy Control on Web Tracking [link]Paper   doi   link   bibtex  
Evasion Attacks Against Statistical Code Obfuscation Detectors. Su, J.; Vargas, D. V.; and Sakurai, K. In Obana, S.; and Chida, K., editor(s), Advances in Information and Computer Security - 12th International Workshop on Security, IWSEC 2017, Hiroshima, Japan, August 30 - September 1, 2017, Proceedings, volume 10418, of Lecture Notes in Computer Science, pages 121–137, 2017. Springer
Evasion Attacks Against Statistical Code Obfuscation Detectors [link]Paper   doi   link   bibtex  
One pixel attack for fooling deep neural networks. Su, J.; Vargas, D. V.; and Sakurai, K. CoRR, abs/1710.08864. 2017.
One pixel attack for fooling deep neural networks [link]Paper   link   bibtex  
  2016 (1)
Curious: Searching for Unknown Regions of Space with a Subpopulation-based Algorithm. Vargas, D. V.; and Murata, J. In Friedrich, T.; Neumann, F.; and Sutton, A. M., editor(s), Genetic and Evolutionary Computation Conference, GECCO 2016, Denver, CO, USA, July 20-24, 2016, Companion Material Proceedings, pages 145–146, 2016. ACM
Curious: Searching for Unknown Regions of Space with a Subpopulation-based Algorithm [link]Paper   doi   link   bibtex  
  2015 (3)
General Subpopulation Framework and Taming the Conflict Inside Populations. Vargas, D. V.; Murata, J.; Takano, H.; and Delbem, A. C. B. Evol. Comput., 23(1): 1–36. 2015.
General Subpopulation Framework and Taming the Conflict Inside Populations [link]Paper   doi   link   bibtex  
Novelty-Organizing Team of Classifiers in noisy and dynamic environments. Vargas, D. V.; Takano, H.; and Murata, J. In IEEE Congress on Evolutionary Computation, CEC 2015, Sendai, Japan, May 25-28, 2015, pages 2937–2944, 2015. IEEE
Novelty-Organizing Team of Classifiers in noisy and dynamic environments [link]Paper   doi   link   bibtex  
The Relationship Between (Un)Fractured Problems and Division of Input Space. Vargas, D. V.; Takano, H.; and Murata, J. In Silva, S.; and Esparcia-Alcázar, A. I., editor(s), Genetic and Evolutionary Computation Conference, GECCO 2015, Madrid, Spain, July 11-15, 2015, Companion Material Proceedings, pages 981–987, 2015. ACM
The Relationship Between (Un)Fractured Problems and Division of Input Space [link]Paper   doi   link   bibtex   1 download  
  2014 (1)
Novelty-organizing classifiers applied to classification and reinforcement learning: towards flexible algorithms. Vargas, D. V.; Takano, H.; and Murata, J. In Arnold, D. V.; and Alba, E., editor(s), Genetic and Evolutionary Computation Conference, GECCO '14, Vancouver, BC, Canada, July 12-16, 2014, Companion Material Proceedings, pages 81–82, 2014. ACM
Novelty-organizing classifiers applied to classification and reinforcement learning: towards flexible algorithms [link]Paper   doi   link   bibtex  
  2013 (4)
Self organizing classifiers: first steps in structured evolutionary machine learning. Vargas, D. V.; Takano, H.; and Murata, J. Evol. Intell., 6(2): 57–72. 2013.
Self organizing classifiers: first steps in structured evolutionary machine learning [link]Paper   doi   link   bibtex  
Self organizing classifiers and niched fitness. Vargas, D. V.; Takano, H.; and Murata, J. In Blum, C.; and Alba, E., editor(s), Genetic and Evolutionary Computation Conference, GECCO '13, Amsterdam, The Netherlands, July 6-10, 2013, pages 1109–1116, 2013. ACM
Self organizing classifiers and niched fitness [link]Paper   doi   link   bibtex  
A study on the importance of selection pressure and low dimensional weak learners to produce robust ensembles. Vargas, D. V.; Takano, H.; and Murata, J. In Blum, C.; and Alba, E., editor(s), Genetic and Evolutionary Computation Conference, GECCO '13, Amsterdam, The Netherlands, July 6-10, 2013, Companion Material Proceedings, pages 1755–1756, 2013. ACM
A study on the importance of selection pressure and low dimensional weak learners to produce robust ensembles [link]Paper   doi   link   bibtex  
Continuous adaptive reinforcement learning with the evolution of Self Organizing Classifiers. Vargas, D. V.; Takano, H.; and Murata, J. In 2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics, ICDL-EPIROB 2013, Osaka, Japan, August 18-22, 2013, pages 1–2, 2013. IEEE
Continuous adaptive reinforcement learning with the evolution of Self Organizing Classifiers [link]Paper   doi   link   bibtex  
  2011 (2)
Phylogenetic Differential Evolution. de Melo, V. V.; Vargas, D. V.; and Crocomo, M. K. Int. J. Nat. Comput. Res., 2(1): 21–38. 2011.
Phylogenetic Differential Evolution [link]Paper   doi   link   bibtex  
Multi-objective Phylogenetic Algorithm: Solving Multi-objective Decomposable Deceptive Problems. Martins, J. P.; Soares, A. H. M.; Vargas, D. V.; and Delbem, A. C. B. In Takahashi, R. H. C.; Deb, K.; Wanner, E. F.; and Greco, S., editor(s), Evolutionary Multi-Criterion Optimization - 6th International Conference, EMO 2011, Ouro Preto, Brazil, April 5-8, 2011. Proceedings, volume 6576, of Lecture Notes in Computer Science, pages 285–297, 2011. Springer
Multi-objective Phylogenetic Algorithm: Solving Multi-objective Decomposable Deceptive Problems [link]Paper   doi   link   bibtex