kernel machine

Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent (Abstract Reprint) AAAI 2026 Adaptive kernel predictors from feature-learning infinite limits of neural networks ICML 2025 AxlePro: Momentum-Accelerated Batched Training of Kernel Machines AISTATS 2025 Joker: Joint Optimization Framework for Lightweight Kernel Machines ICML 2025 Tensor Network-Constrained Kernel Machines as Gaussian Processes AISTATS 2025 On Statistical Learning Theory for Distributional Inputs ICML 2024 On the Nyström Approximation for Preconditioning in Kernel Machines AISTATS 2024 Position: Tensor Networks are a Valuable Asset for Green AI ICML 2024 Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models AISTATS 2024 Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification AAAI 2024 Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation NeurIPS 2023 Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data AISTATS 2023 Toward Large Kernel Models ICML 2023 Knowledge Distillation: Bad Models Can Be Good Role Models NeurIPS 2022 Understanding and Mitigating Data Contamination in Deep Anomaly Detection: A Kernel-based Approach IJCAI 2022 Conjugate Gradients for Kernel Machines JMLR 2020 Hard Shape-Constrained Kernel Machines NeurIPS 2020 Kernel Machines Beat Deep Neural Networks on Mask-Based Single-Channel Speech Enhancement Interspeech 2019 Clustering Induced Kernel Learning ACML 2018 KELP: a Kernel-based Learning Platform JMLR 2018 Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate NeurIPS 2018 To Understand Deep Learning We Need to Understand Kernel Learning ICML 2018 Computationally Efficient Nyström Approximation using Fast Transforms ICML 2016 Learning Kernels with Random Features NeurIPS 2016 Preconditioning Kernel Matrices ICML 2016