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Johan A. K. Suykens

  1. Identification of stable models in subspace identification by using regularization
    2001/01/01 by Tony Van Gestel, T. Van Gestel, J.A.K. Suykens +5 · 4 citations
    Engineering · #Control Systems and Identification #Structural Health Monitoring Techniques #Fault Detection and Control Systems
  2. Fast and Scalable Lasso via Stochastic Frank-Wolfe Methods with a\n Convergence Guarantee
    2015/10/24 by Emanuele Frandi, Frandi, Emanuele, Ricardo Ñanculef +6 · 2 citations
    Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Optimization and Control (math.OC) #Statistical Methods and Inference #Stochastic Gradient Optimization Techniques
  3. Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
    2023/05/31 by Yingyi Chen, Chen, Yingyi, Qinghua Tao +5 · 2 citations
    Computer Science · #Advanced Neural Network Applications #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning and ELM
  4. Unbalanced Optimal Transport: A Unified Framework for Object Detection
    2023/07/05 by Henri De Plaen, Pierre-François De Plaen, De Plaen, Henri +9 · 2 citations
    Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  5. Learning Tensors in Reproducing Kernel Hilbert Spaces with Multilinear Spectral Penalties
    2013/10/18 by Marco Signoretto, Lieven De Lathauwer, Signoretto, Marco +3 · 1 citation
    Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Speech Recognition and Synthesis #Tensor decomposition and applications
  6. Disentangled Representation Learning and Generation with Manifold Optimization
    2020/06/12 by Arun Pandey, Michaël Fanuel, Pandey, Arun +5 · 1 citation
    Computer Science · #Generative Adversarial Networks and Image Synthesis #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI)
  7. Boosting Co-teaching with Compression Regularization for Label Noise
    2021/04/28 by Yingyi Chen, Xi Shen, Chen, Yingyi +5 · 1 citation
    Computer Science · Engineering · #Machine Learning and Data Classification #Advanced Neural Network Applications #Industrial Vision Systems and Defect Detection
  8. Compressing Features for Learning with Noisy Labels
    2022/06/27 by Yingyi Chen, Chen, Yingyi, Shell Xu Hu +7 · 1 citation
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  9. Spatio-temporal Stacked LSTM for Temperature Prediction in Weather Forecasting
    2018/11/15 by Zahra Karevan, Johan A. K. Suykens, Karevan, Zahra +1 · 1 citation
    Computer Science · Environmental Science · #Time Series Analysis and Forecasting #Music and Audio Processing #Hydrological Forecasting Using AI
  10. Parallelized Tensor Train Learning of Polynomial Classifiers
    2016/12/20 by Zhongming Chen, Kim Batselier, Chen, Zhongming +5 · 1 citation
    Mathematics · Computer Science · #Tensor decomposition and applications #Parallel Computing and Optimization Techniques #Computational Physics and Python Applications
  11. Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive Kernels
    2023/10/08 by Fan He, He, Fan, Mingzhen He +7 · 1 citation
    Computer Science · #Machine Learning and ELM #Neural Networks and Applications #Face and Expression Recognition
  12. Nonlinear functional regression by functional deep neural network with kernel embedding
    2024/01/05 by Zhongjie Shi, Jun Fan, Shi, Zhongjie +7 · 1 citation
    Computer Science · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Neural Networks and Applications
  13. Deep Kernel Principal Component Analysis for Multi-level Feature Learning
    2023/02/22 by Francesco Tonin, Qinghua Tao, Tonin, Francesco +5 · 1 citation
    Computer Science · #Blind Source Separation Techniques #FOS: Computer and information sciences #Face and Expression Recognition #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG)
  14. Deep Adaptive Bayesian Screening
    2026/07/18 by Jade Lejeune Herman, Arno Strouwen, Johan A. K. Suykens +1
    #stat.ML #cs.LG