Minyoung Kim

99 papers A* 25A 4B 1Journal 64Unranked 5
YearRankTypeTitle / Venue / Authors
2026 A* conf
FedP²EFT: Federated Learning to Personalize PEFT for Multilingual LLMs.
AAAI
Royson Lee, Minyoung Kim, Fady Rezk, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales
2025 A* conf
A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning.
AAAI
Minyoung Kim, Timothy M. Hospedales
2025 J jnl
FedHB: Hierarchical Bayesian Federated Learning.
J. Mach. Learn. Res.
Minyoung Kim, Timothy M. Hospedales
2025 J jnl
FedP
CoRR
Royson Lee, Minyoung Kim, Fady Rezk, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales
2025 A* conf
LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning.
ICLR
Minyoung Kim, Timothy M. Hospedales
2025 J jnl
Model Diffusion for Certifiable Few-shot Transfer Learning.
CoRR
Fady Rezk, Royson Lee, Henry Gouk, Timothy M. Hospedales, Minyoung Kim
2025 J jnl
Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning.
CoRR
Taehoon Kim, Henry Gouk, Minyoung Kim, Timothy M. Hospedales
2024 A* conf
A Bayesian Approach to Data Point Selection.
NeurIPS
Xinnuo Xu, Minyoung Kim, Royson Lee, Brais Martínez, Timothy M. Hospedales
2024 J jnl
A Bayesian Approach to Data Point Selection.
CoRR
Xinnuo Xu, Minyoung Kim, Royson Lee, Brais Martínez, Timothy M. Hospedales
2024 A* conf
A Hierarchical Bayesian Model for Few-Shot Meta Learning.
ICLR
Minyoung Kim, Timothy M. Hospedales
2024 J jnl
A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning.
CoRR
Minyoung Kim, Timothy M. Hospedales
2023 J jnl
A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning.
CoRR
Minyoung Kim, Timothy M. Hospedales
2023 J jnl
BayesDLL: Bayesian Deep Learning Library.
CoRR
Minyoung Kim, Timothy M. Hospedales
2023 A* conf
BayesTune: Bayesian Sparse Deep Model Fine-tuning.
NeurIPS
Minyoung Kim, Timothy M. Hospedales
2023 A* conf
Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach.
ICLR
Minyoung Kim, Da Li, Timothy M. Hospedales
2023 J jnl
Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach.
CoRR
Minyoung Kim, Da Li, Timothy M. Hospedales
2023 J jnl
FedHB: Hierarchical Bayesian Federated Learning.
CoRR
Minyoung Kim, Timothy M. Hospedales
2023 A* conf
FedL2P: Federated Learning to Personalize.
NeurIPS
Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszar, Nicholas D. Lane
2023 J jnl
FedL2P: Federated Learning to Personalize.
CoRR
Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
2023 A conf
SwAMP: Swapped Assignment of Multi-Modal Pairs for Cross-Modal Retrieval.
AISTATS
Minyoung Kim
2022 A* conf
Differentiable Expectation-Maximization for Set Representation Learning.
ICLR
Minyoung Kim
2022 A* conf
Fisher SAM: Information Geometry and Sharpness Aware Minimisation.
ICML
Minyoung Kim, Da Li, Shell Xu Hu, Timothy M. Hospedales
2022 J jnl
Fisher SAM: Information Geometry and Sharpness Aware Minimisation.
CoRR
Minyoung Kim, Da Li, Shell Xu Hu, Timothy M. Hospedales
2022 A* conf
Gaussian Process Modeling of Approximate Inference Errors for Variational Autoencoders.
CVPR
Minyoung Kim
2022 A* conf
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference.
CVPR
Shell Xu Hu, Da Li, Jan Stühmer, Minyoung Kim, Timothy M. Hospedales
2022 J jnl
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference.
CoRR
Shell Xu Hu, Da Li, Jan Stühmer, Minyoung Kim, Timothy M. Hospedales
2022 A conf
Variational Continual Proxy-Anchor for Deep Metric Learning.
AISTATS
Minyoung Kim, Ricardo Guerrero, Hai Xuan Pham, Vladimir Pavlovic
2021 J jnl
Gaussian Process Meta Few-shot Classifier Learning via Linear Discriminant Laplace Approximation.
CoRR
Minyoung Kim, Timothy M. Hospedales
2021 A* conf
Learning Disentangled Factors from Paired Data in Cross-Modal Retrieval: An Implicit Identifiable VAE Approach.
ACM Multimedia
Minyoung Kim, Ricardo Guerrero, Vladimir Pavlovic
2021 J jnl
On PyTorch Implementation of Density Estimators for von Mises-Fisher and Its Mixture.
CoRR
Minyoung Kim
2021 J jnl
Reducing the Amortization Gap in Variational Autoencoders: A Bayesian Random Function Approach.
CoRR
Minyoung Kim, Vladimir Pavlovic
2021 J jnl
SwAMP: Swapped Assignment of Multi-Modal Pairs for Cross-Modal Retrieval.
CoRR
Minyoung Kim
2020 J jnl
Learning Disentangled Latent Factors from Paired Data in Cross-Modal Retrieval: An Implicit Identifiable VAE Approach.
CoRR
Minyoung Kim, Ricardo Guerrero, Vladimir Pavlovic
2020 A* conf
Ordinal-Content VAE: Isolating Ordinal-Valued Content Factors in Deep Latent Variable Models.
ICDM
Minyoung Kim, Vladimir Pavlovic
2020 J jnl
Ordinal-Content VAE: Isolating Ordinal-Valued Content Factors in Deep Latent Variable Models.
CoRR
Minyoung Kim, Vladimir Pavlovic
2020 A* conf
Recursive Inference for Variational Autoencoders.
NeurIPS
Minyoung Kim, Vladimir Pavlovic
2020 J jnl
Recursive Inference for Variational Autoencoders.
CoRR
Minyoung Kim, Vladimir Pavlovic
2019 A* conf
Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement.
ICCV
Minyoung Kim, Yuting Wang, Pritish Sahu, Vladimir Pavlovic
2019 J jnl
Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement.
CoRR
Minyoung Kim, Yuting Wang, Pritish Sahu, Vladimir Pavlovic
2019 J jnl
Efficient Deep Gaussian Process Models for Variable-Sized Input.
CoRR
Issam H. Laradji, Mark Schmidt, Vladimir Pavlovic, Minyoung Kim
2019 B conf
Efficient Deep Gaussian Process Models for Variable-Sized Inputs.
IJCNN
Issam H. Laradji, Mark Schmidt, Vladimir Pavlovic, Minyoung Kim
2019 J jnl
Large-margin learning of Cox proportional hazard models for survival analysis.
Appl. Intell.
Minyoung Kim
2019 J jnl
Relevance Factor VAE: Learning and Identifying Disentangled Factors.
CoRR
Minyoung Kim, Yuting Wang, Pritish Sahu, Vladimir Pavlovic
2019 J jnl
Sparse large-margin nearest neighbor embedding via greedy dyad functional optimization.
Appl. Intell.
Minyoung Kim
2019 — conf
Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation.
ICCV Workshops
Behnam Gholami, Pritish Sahu, Minyoung Kim, Vladimir Pavlovic
2019 J jnl
Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation.
CoRR
Behnam Gholami, Pritish Sahu, Minyoung Kim, Vladimir Pavlovic
2019 A* conf
Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach.
CVPR
Minyoung Kim, Pritish Sahu, Behnam Gholami, Vladimir Pavlovic
2019 J jnl
Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach.
CoRR
Minyoung Kim, Pritish Sahu, Behnam Gholami, Vladimir Pavlovic
2018 J jnl
A maximum-likelihood and moment-matching density estimator for crowd-sourcing label prediction.
Appl. Intell.
Minyoung Kim
2018 J jnl
Dynamic sparse coding for sparse time-series modeling via first-order smooth optimization.
Appl. Intell.
Minyoung Kim
2018 A* conf
Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data.
ICML
Minyoung Kim
2018 A conf
Variational Inference for Gaussian Process Models for Survival Analysis.
UAI
Minyoung Kim, Vladimir Pavlovic
2017 J jnl
Dual soft assignment clustering algorithm for human action video clustering.
Comput. Vis. Image Underst.
Minyoung Kim
2017 J jnl
Efficient histogram dictionary learning for text/image modeling and classification.
Data Min. Knowl. Discov.
Minyoung Kim
2017 J jnl
Mixtures of Conditional Random Fields for Improved Structured Output Prediction.
IEEE Trans. Neural Networks Learn. Syst.
Minyoung Kim
2017 J jnl
Simultaneous Kernel Learning and Label Imputation for Pattern Classification with Partially Labeled Data.
Int. J. Fuzzy Log. Intell. Syst.
Minyoung Kim
2017 J jnl
Simultaneous Learning of Sentence Clustering and Class Prediction for Improved Document Classification.
Int. J. Fuzzy Log. Intell. Syst.
Minyoung Kim
2016 J jnl
Adaptive Bayesian Object Tracking with Histograms of Dense Local Image Descriptors.
Int. J. Fuzzy Log. Intell. Syst.
Minyoung Kim
2016 J jnl
Document Summarization via Convex-Concave Programming.
Int. J. Fuzzy Log. Intell. Syst.
Minyoung Kim
2016 J jnl
Model-induced term-weighting schemes for text classification.
Appl. Intell.
Hyun Kyung Kim, Minyoung Kim
2016 J jnl
Robust Algorithms for Combining Multiple Term Weighting Vectors for Document Classification.
Int. J. Fuzzy Log. Intell. Syst.
Minyoung Kim
2016 J jnl
Sparse conditional copula models for structured output regression.
Pattern Recognit.
Minyoung Kim
2016 J jnl
Sparse inverse covariance learning of conditional Gaussian mixtures for multiple-output regression.
Appl. Intell.
Minyoung Kim
2015 J jnl
Greedy approaches to semi-supervised subspace learning.
Pattern Recognit.
Minyoung Kim
2015 J jnl
Greedy ensemble learning of structured predictors for sequence tagging.
Neurocomputing
Minyoung Kim
2015 J jnl
Multiple-concept feature generative models for multi-label image classification.
Comput. Vis. Image Underst.
Minyoung Kim
2015 J jnl
Online Selective-Sample Learning of Hidden Markov Models for Sequence Classification.
Int. J. Fuzzy Log. Intell. Syst.
Minyoung Kim
2015 J jnl
Sparse discriminative region selection algorithm for face recognition.
Appl. Intell.
Minyoung Kim
2014 J jnl
Conditional ordinal random fields for structured ordinal-valued label prediction.
Data Min. Knowl. Discov.
Minyoung Kim
2014 J jnl
Discriminative Training of Sequence Taggers via Local Feature Matching.
Int. J. Fuzzy Log. Intell. Syst.
Minyoung Kim
2014 J jnl
Efficient Kernel Sparse Coding Via First-Order Smooth Optimization.
IEEE Trans. Neural Networks Learn. Syst.
Minyoung Kim
2014 J jnl
Greedy Learning of Sparse Eigenfaces for Face Recognition and Tracking.
Int. J. Fuzzy Log. Intell. Syst.
Minyoung Kim
2014 J jnl
Multiple instance learning via Gaussian processes.
Data Min. Knowl. Discov.
Minyoung Kim, Fernando De la Torre
2014 J jnl
Probabilistic Sequence Translation-Alignment Model for Time-Series Classification.
IEEE Trans. Knowl. Data Eng.
Minyoung Kim
2014 J jnl
Robust Video-Based Barcode Recognition via Online Sequential Filtering.
Int. J. Fuzzy Log. Intell. Syst.
Minyoung Kim
2013 J jnl
Accelerated max-margin multiple kernel learning.
Appl. Intell.
Minyoung Kim
2013 J jnl
Conditional Alignment Random Fields for Multiple Motion Sequence Alignment.
IEEE Trans. Pattern Anal. Mach. Intell.
Minyoung Kim
2013 J jnl
Semi-Supervised Recursive Learning of Discriminative Mixture Models for Time-Series Classification.
Int. J. Fuzzy Log. Intell. Syst.
Minyoung Kim
2013 J jnl
Semi-supervised learning of hidden conditional random fields for time-series classification.
Neurocomputing
Minyoung Kim
2012 J jnl
Correlation-based incremental visual tracking.
Pattern Recognit.
Minyoung Kim
2012 J jnl
Time-Series Dimensionality Reduction via Granger Causality.
IEEE Signal Process. Lett.
Minyoung Kim
2011 J jnl
Central Subspace Dimensionality Reduction Using Covariance Operators.
IEEE Trans. Pattern Anal. Mach. Intell.
Minyoung Kim, Vladimir Pavlovic
2011 J jnl
Discriminative semi-supervised learning of dynamical systems for motion estimation.
Pattern Recognit.
Minyoung Kim
2011 J jnl
Sequence Alignment by Regression Coding.
IEEE Signal Process. Lett.
Minyoung Kim
2011 J jnl
Sequence classification via large margin hidden Markov models.
Data Min. Knowl. Discov.
Minyoung Kim, Vladimir Pavlovic
2010 — conf
A Real-Time System for Head Tracking and Pose Estimation.
ECCV Workshops (1)
Zengyin Zhang, Minyoung Kim, Fernando De la Torre, Wende Zhang
2010 A* conf
Gaussian Processes Multiple Instance Learning.
ICML
Minyoung Kim, Fernando De la Torre
2010 — conf
Hidden Conditional Ordinal Random Fields for Sequence Classification.
ECML/PKDD (2)
Minyoung Kim, Vladimir Pavlovic
2010 J jnl
Large margin cost-sensitive learning of conditional random fields.
Pattern Recognit.
Minyoung Kim
2010 A* conf
Local Minima Embedding.
ICML
Minyoung Kim, Fernando De la Torre
2010 — conf
Structured Output Ordinal Regression for Dynamic Facial Emotion Intensity Prediction.
ECCV (3)
Minyoung Kim, Vladimir Pavlovic
2009 A conf
Covariance Operator Based Dimensionality Reduction with Extension to Semi-Supervised Settings.
AISTATS
Minyoung Kim, Vladimir Pavlovic
2009 J jnl
Discriminative Learning for Dynamic State Prediction.
IEEE Trans. Pattern Anal. Mach. Intell.
Minyoung Kim, Vladimir Pavlovic
2008 A* conf
Dimensionality reduction using covariance operator inverse regression.
CVPR
Minyoung Kim, Vladimir Pavlovic
2008 A* conf
Face tracking and recognition with visual constraints in real-world videos.
CVPR
Minyoung Kim, Sanjiv Kumar, Vladimir Pavlovic, Henry A. Rowley
2007 A* conf
A recursive method for discriminative mixture learning.
ICML
Minyoung Kim, Vladimir Pavlovic
2007 A* conf
Conditional State Space Models for Discriminative Motion Estimation.
ICCV
Minyoung Kim, Vladimir Pavlovic
2007 A* conf
Discriminative Learning of Dynamical Systems for Motion Tracking.
CVPR
Minyoung Kim, Vladimir Pavlovic
2006 — conf
Discriminative Learning of Mixture of Bayesian Network Classifiers for Sequence Classification.
CVPR (1)
Minyoung Kim, Vladimir Pavlovic