Xiaolin Huang
27 papers · 2014–2026 · 9 venues · across top CS/AI venues
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Machine Learning
(24)
Optimization & Theory Β· Machine Learning
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Deep Learning
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Core AI
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kernel methods
(3)
deep neural network
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adversarial training
(2)
capsule network
(2)
reproducing kernel hilbert space
(2)
non-convex optimization
(2)
adversarial perturbation
(2)
adversarial attack
(2)
out-of-distribution detection
(2)
neural network optimization
(2)
kernel ridge regression
(2)
dynamic routing
(1)
privacy preservation
(1)
machine unlearning
(1)
neural network training
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benchmark evaluation
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model robustness
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kernel learning
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matrix factorization
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Papers
VL-RouterBench: A Benchmark for Vision-Language Model Routing
CVPR 2026
Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
ICML 2025
ParseCaps: An Interpretable Parsing Capsule Network for Medical Image Diagnosis
AAAI 2025
Primphormer: Efficient Graph Transformers with Primal Representations
ICML 2025
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection
ICLR 2025
Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks
ICLR 2025
Friendly Sharpness-Aware Minimization
CVPR 2024
Kernel PCA for Out-of-Distribution Detection
NeurIPS 2024
Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy
ECCV 2024
OrthCaps: An Orthogonal CapsNet with Sparse Attention Routing and Pruning
CVPR 2024
Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement
NeurIPS 2024
Better Loss Landscape Visualization for Deep Neural Networks with Trajectory Information
ACML 2023
Diffusion Representation for Asymmetric Kernels via Magnetic Transform
NeurIPS 2023
One-Pixel Shortcut: On the Learning Preference of Deep Neural Networks
ICLR 2023
Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors
ICLR 2023
Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions
ICLR 2023
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks
NeurIPS 2022
PCR-CG: Point Cloud Registration via Deep Explicit Color and Geometry
ECCV 2022
Subspace Adversarial Training
CVPR 2022
Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures
AISTATS 2021
Generalization Properties of hyper-RKHS and its Applications
JMLR 2021
A Generalized Framework for Edge-Preserving and Structure-Preserving Image Smoothing
AAAI 2020
Learning Data-adaptive Non-parametric Kernels
JMLR 2020
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling
AAAI 2020
Sparse Kernel Regression with Coefficient-based β_q-regularization
JMLR 2019
Learning with the Maximum Correntropy Criterion Induced Losses for Regression
JMLR 2015
Ramp Loss Linear Programming Support Vector Machine
JMLR 2014