Xiaolin Huang
26 papers · 2014–2025 · 9 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (11) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird
🌍
Conference Polyglot
(9)
🏃
Academic Marathon
(11)
🧭
Keyword Pioneer
🏆
Grand Slam
🗃️
Keyword Collector
(99)
💎
Century Club
(26)
🔥
Unstoppable
(7)
⚡
Prolific Year
(5)
Conferences
ICLR (5)
JMLR (5)
NIPS (4)
AAAI (3)
CVPR (3)
ECCV (2)
ICML (2)
ACML (1)
AISTATS (1)
Top co-authors
Research topics
Keywords
kernel methods
(3)
reproducing kernel hilbert space
(2)
adversarial attack
(2)
capsule network
(2)
kernel ridge regression
(2)
non-convex optimization
(2)
matrix factorization
(1)
principal component analysis
(1)
robust regression
(1)
dynamic routing
(1)
machine unlearning
(1)
sharpness-aware minimization
(1)
model forgetting
(1)
loss landscape
(1)
hierarchical representation
(1)
adversarial training
(1)
dimension reduction
(1)
medical image classification
(1)
privacy preservation
(1)
kernel approximation
(1)
Papers
Primphormer: Efficient Graph Transformers with Primal Representations
ICML 2025
ParseCaps: An Interpretable Parsing Capsule Network for Medical Image Diagnosis
AAAI 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
Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
ICML 2025
Kernel PCA for Out-of-Distribution Detection
NIPS 2024
OrthCaps: An Orthogonal CapsNet with Sparse Attention Routing and Pruning
CVPR 2024
Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement
NIPS 2024
Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy
ECCV 2024
Friendly Sharpness-Aware Minimization
CVPR 2024
Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors
ICLR 2023
One-Pixel Shortcut: On the Learning Preference of Deep Neural Networks
ICLR 2023
Better Loss Landscape Visualization for Deep Neural Networks with Trajectory Information
ACML 2023
Diffusion Representation for Asymmetric Kernels via Magnetic Transform
NIPS 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
NIPS 2022
Subspace Adversarial Training
CVPR 2022
PCR-CG: Point Cloud Registration via Deep Explicit Color and Geometry
ECCV 2022
Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures
AISTATS 2021
Generalization Properties of hyper-RKHS and its Applications
JMLR 2021
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling
AAAI 2020
Learning Data-adaptive Non-parametric Kernels
JMLR 2020
A Generalized Framework for Edge-Preserving and Structure-Preserving Image Smoothing
AAAI 2020
Sparse Kernel Regression with Coefficient-based $\ell_q-$regularization
JMLR 2019
Learning with the Maximum Correntropy Criterion Induced Losses for Regression
JMLR 2015
Ramp Loss Linear Programming Support Vector Machine
JMLR 2014