Jingwen Ye
22 papers · 2019–2025 · 7 venues · across top CS/AI venues
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Research topics
Machine Learning
(17)
Deep Learning
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Artificial Intelligence
(9)
Learning Types Β· Machine Learning
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Learning Types Β· Deep Learning
(9)
Architectures
(5)
Core AI
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Learning Paradigms
(4)
Computer Vision
(3)
Analysis
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Models
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Optimization & Theory
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Core Methods
(2)
Keywords
knowledge distillation
(11)
model compression
(6)
convolutional neural network
(4)
transfer learning
(4)
multi-task learning
(3)
neural network
(3)
adversarial learning
(2)
synthetic data
(2)
feature learning
(2)
knowledge amalgamation
(2)
gradient matching
(2)
adversarial attack
(2)
knowledge transfer
(2)
dataset distillation
(2)
computer vision
(1)
pose estimation
(1)
adversarial robustness
(1)
machine unlearning
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online learning
(1)
data-free learning
(1)
Papers
Heavy Labels Out! Dataset Distillation with Label Space Lightening
ICCV 2025
Distilled Datamodel with Reverse Gradient Matching
CVPR 2024
Improving Adversarial Robustness via Feature Pattern Consistency Constraint
IJCAI 2024
Model LEGO: Creating Models Like Disassembling and Assembling Building Blocks
NeurIPS 2024
Mutual-Modality Adversarial Attack with Semantic Perturbation
AAAI 2024
StyDeSty: Min-Max Stylization and Destylization for Single Domain Generalization
ICML 2024
Teddy: Efficient Large-Scale Dataset Distillation via Taylor-Approximated Matching
ECCV 2024
Transformer Doctor: Diagnosing and Treating Vision Transformers
NeurIPS 2024
Ungeneralizable Examples
CVPR 2024
Partial Network Cloning
CVPR 2023
Slimmable Dataset Condensation
CVPR 2023
Dataset Distillation via Factorization
NeurIPS 2022
Deep Model Reassembly
NeurIPS 2022
DynaST: Dynamic Sparse Transformer for Exemplar-Guided Image Generation
ECCV 2022
Factorizing Knowledge in Neural Networks
ECCV 2022
Learning with Recoverable Forgetting
ECCV 2022
Safe Distillation Box
AAAI 2022
Online Knowledge Distillation for Efficient Pose Estimation
ICCV 2021
Data-Free Knowledge Amalgamation via Group-Stack Dual-GAN
CVPR 2020
DEPARA: Deep Attribution Graph for Deep Knowledge Transferability
CVPR 2020
Amalgamating Filtered Knowledge: Learning Task-customized Student from Multi-task Teachers
IJCAI 2019
Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation, and More
CVPR 2019