Johan Suykens
12 papers · 2007–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (18) π§ Keyword Pioneer π Interdisciplinary Bridge π Conference Polyglot (4) π Cross-Pollinator (8)
π§
Keyword Pioneer
π
Conference Polyglot
(4)
π
Keyword Champion
π
Trend Setter
π
Century Club
(12)
π₯
Unstoppable
(6)
Conferences
ICML (4)
NIPS (4)
AISTATS (3)
AAAI (1)
Top co-authors
Keywords
kernel methods
(4)
kernel ridge regression
(2)
random feature
(2)
double descent
(2)
model architecture
(1)
neural network optimization
(1)
stochastic gradient descent
(1)
nonparametric learning
(1)
kernel principal component analysis
(1)
risk minimization
(1)
kernel pca
(1)
reproducing kernel hilbert space
(1)
gradient descent
(1)
margin maximization
(1)
high-dimensional regression
(1)
low-rank approximation
(1)
rademacher complexity
(1)
high-dimensional analysis
(1)
margin classification
(1)
singular value decomposition
(1)
Papers
Accelerating Spectral Clustering under Fairness Constraints
ICML 2025
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and NystrΓΆm method
ICML 2024
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
ICML 2024
Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms
ICML 2023
Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
NIPS 2023
On the Double Descent of Random Features Models Trained with SGD
NIPS 2022
Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures
AISTATS 2021
Kernel regression in high dimensions: Refined analysis beyond double descent
AISTATS 2021
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling
AAAI 2020
A Theoretical Framework for Target Propagation
NIPS 2020
Solving lp-norm regularization with tensor kernels
AISTATS 2018
A Risk Minimization Principle for a Class of Parzen Estimators
NIPS 2007