Minyoung Kim
24 papers · 2005–2026 · 12 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (44) 🌍 Conference Polyglot · Gold 🏃 Academic Marathon · Ultra 🌉 Interdisciplinary Bridge · Bronze 🏆 Grand Slam
🧬
Topic Evolution
🤝
Dynamic Duo
(11)
🗃️
Keyword Collector
(99)
🔥
Unstoppable · Bronze
⚡
Prolific Year · Productive
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Conference Pioneer
💎
Century Club · Bronze
Venues
Top co-authors
Research topics
Artificial Intelligence
(15)
Machine Learning
(14)
Deep Learning
(11)
Optimization & Theory · Machine Learning
(10)
Learning Paradigms
(8)
Bayesian & Probabilistic
(7)
Learning Types · Machine Learning
(7)
Models
(5)
Core Methods
(4)
Learning Types · Deep Learning
(3)
Optimization & Theory · Deep Learning
(3)
Application Areas
(2)
Core AI
(2)
Natural Language Processing
(1)
Speech & Audio
(1)
Keywords
bayesian inference
(6)
variational inference
(5)
few-shot learning
(3)
variational autoencoder
(3)
gaussian process
(3)
federated learning
(3)
domain adaptation
(2)
mixture model
(2)
stochastic gradient langevin dynamics
(2)
parameter-efficient fine-tuning
(2)
posterior approximation
(2)
posterior distribution
(2)
amortized inference
(2)
computer vision
(1)
image classification
(1)
transfer learning
(1)
langevin dynamics
(1)
unsupervised learning
(1)
domain generalization
(1)
convergence analysis
(1)
Papers
FedP²EFT: Federated Learning to Personalize PEFT for Multilingual LLMs
AAAI 2026
Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning
UAI 2026
A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning
AAAI 2025
Cross-Modal Watermarking for Authentic Audio Recovery and Tamper Localization in Synthesized Audiovisual Forgeries
Interspeech 2025
FedHB: Hierarchical Bayesian Federated Learning
JMLR 2025
LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning
ICLR 2025
ReSCORE: Label-free Iterative Retriever Training for Multi-hop Question Answering with Relevance-Consistency Supervision
ACL 2025
A Bayesian Approach to Data Point Selection
NeurIPS 2024
A Hierarchical Bayesian Model for Few-Shot Meta Learning
ICLR 2024
BayesTune: Bayesian Sparse Deep Model Fine-tuning
NeurIPS 2023
Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach
ICLR 2023
FedL2P: Federated Learning to Personalize
NeurIPS 2023
SwAMP: Swapped Assignment of Multi-Modal Pairs for Cross-Modal Retrieval
AISTATS 2023
Differentiable Expectation-Maximization for Set Representation Learning
ICLR 2022
Fisher SAM: Information Geometry and Sharpness Aware Minimisation
ICML 2022
Gaussian Process Modeling of Approximate Inference Errors for Variational Autoencoders
CVPR 2022
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference
CVPR 2022
Variational Continual Proxy-Anchor for Deep Metric Learning
AISTATS 2022
Recursive Inference for Variational Autoencoders
NeurIPS 2020
Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement
ICCV 2019
Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach
CVPR 2019
Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data
ICML 2018
Online Multi-Object Tracking with Dual Matching Attention Networks
ECCV 2018
Covariance Operator Based Dimensionality Reduction with Extension to Semi-Supervised Settings
AISTATS 2005