Minyoung Kim

发表

Face tracking and recognition with visual constraints in real-world videos

Vladimir Pavlovic, Sanjiv Kumar, Minyoung Kim, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Gaussian Processes Multiple Instance Learning

Fernando De la Torre, Minyoung Kim, Minyoung Kim, 2010, ICML.

Conditional State Space Models for Discriminative Motion Estimation

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2007, 2007 IEEE 11th International Conference on Computer Vision.

Discriminative Learning of Generative Models for Sequence Classification and Motion Tracking

Minyoung Kim, 2007 .

Discriminative Learning of Probabilistic Sequence Models for Sequence Labeling Problems

James M. Rehg, Minyoung Kim, V. Pavlovic, 2006 .

LG ] 6 M ar 2 01 5 Deep Clustered Convolutional Kernels

Minyoung Kim, L. Rigazio, 2018 .

Cost-Sensitive Estimation of ARMA Models for Financial Asset Return Data

Minyoung Kim, 2015 .

Variational Continual Proxy-Anchor for Deep Metric Learning

Minyoung Kim, V. Pavlovic, Ricardo Guerrero, 2022, AISTATS.

Fisher SAM: Information Geometry and Sharpness Aware Minimisation

Timothy M. Hospedales, Minyoung Kim, Da Li, 2022, ICML.

Accelerated max-margin multiple kernel learning

Minyoung Kim, 2012, Applied Intelligence.

Sparse large-margin nearest neighbor embedding via greedy dyad functional optimization

Minyoung Kim, 2019, Applied Intelligence.

Differentiable Expectation-Maximization for Set Representation Learning

Minyoung Kim, 2022, ICLR.

Efficient Kernel Sparse Coding Via First-Order Smooth Optimization

Minyoung Kim, Minyoung Kim, 2014, IEEE Transactions on Neural Networks and Learning Systems.

Deep Clustered Convolutional Kernels pdf

Minyoung Kim, Luca Rigazio, Minyoung Kim, 2015, FE@NIPS.

Structured Output Ordinal Regression for Dynamic Facial Emotion Intensity Prediction

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2010, ECCV.

Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference

Timothy M. Hospedales, Minyoung Kim, Da Li, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Large-margin learning of Cox proportional hazard models for survival analysis

Minyoung Kim, Minyoung Kim, 2018, Applied Intelligence.

Semi-supervised learning of hidden conditional random fields for time-series classification

Minyoung Kim, Minyoung Kim, 2013, Neurocomputing.

Central Subspace Dimensionality Reduction Using Covariance Operators

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Real-Time System for Head Tracking and Pose Estimation

Fernando De la Torre, Minyoung Kim, Wende Zhang, 2010, ECCV Workshops.

Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement

Vladimir Pavlovic, Minyoung Kim, Pritish Sahu, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Relevance Factor VAE: Learning and Identifying Disentangled Factors pdf

Vladimir Pavlovic, Minyoung Kim, Yuting Wang, 2019, ArXiv.

Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach

Timothy M. Hospedales, Minyoung Kim, Da Li, 2023, ICLR.

Dynamic sparse coding for sparse time-series modeling via first-order smooth optimization

Minyoung Kim, Minyoung Kim, 2018, Applied Intelligence.

Online Multi-Object Tracking with Dual Matching Attention Networks pdf

Hua Yang, Ming-Hsuan Yang, Wenjun Zhang, 2018, ECCV.

Stefano Alletto, Minyoung Kim, Luca Rigazio, 2016, ArXiv.

Multiple instance learning via Gaussian processes

Fernando De la Torre, Minyoung Kim, Minyoung Kim, 2014, Data Mining and Knowledge Discovery.

Model-induced term-weighting schemes for text classification

Minyoung Kim, Hyun Kyung Kim, Minyoung Kim, 2016, Applied Intelligence.

Gaussian Process Meta Few-shot Classifier Learning via Linear Discriminant Laplace Approximation pdf

Timothy Hospedales, Minyoung Kim, Timothy M. Hospedales, 2021, ArXiv.

Greedy Learning of Sparse Eigenfaces for Face Recognition and Tracking

Minyoung Kim, Minyoung Kim, 2014, Int. J. Fuzzy Log. Intell. Syst..

Greedy approaches to semi-supervised subspace learning

Minyoung Kim, Minyoung Kim, 2015, Pattern Recognit..

Conditional Alignment Random Fields for Multiple Motion Sequence Alignment

Minyoung Kim, Minyoung Kim, 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning

Timothy M. Hospedales, Minyoung Kim, 2023, ArXiv.

Model-induced term-weighting schemes for text classification

Minyoung Kim, Hyun Kyung Kim, 2016, Applied Intelligence.

Dynamic sparse coding for sparse time-series modeling via first-order smooth optimization

Minyoung Kim, 2018, Applied Intelligence.

A recursive method for discriminative mixture learning

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2007, ICML '07.

Efficient histogram dictionary learning for text/image modeling and classification

Minyoung Kim, Minyoung Kim, 2016, Data Mining and Knowledge Discovery.

Dimensionality reduction using covariance operator inverse regression

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Efficient Deep Gaussian Process Models for Variable-Sized Inputs

Vladimir Pavlovic, Mark W. Schmidt, Mark Schmidt, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Online Multi-Object Tracking with Dual Matching Attention Networks

Ming-Hsuan Yang, Minyoung Kim, Wenjun Zhang, 2018, ECCV.

Gradient-based cell localization for automated stem cell counting in non-fluorescent images

Minyoung Kim, Minjung Song, Minyoung Kim, 2014, Tissue Engineering and Regenerative Medicine.

Online Selective-Sample Learning of Hidden Markov Models for Sequence Classification

Minyoung Kim, Minyoung Kim, 2015, Int. J. Fuzzy Log. Intell. Syst..

Probabilistic Sequence Translation-Alignment Model for Time-Series Classification

Minyoung Kim, Minyoung Kim, 2014, IEEE Transactions on Knowledge and Data Engineering.

Semi-Supervised Recursive Learning of Discriminative Mixture Models for Time-Series Classification

Minyoung Kim, Minyoung Kim, 2013, Int. J. Fuzzy Log. Intell. Syst..

Sequence classification via large margin hidden Markov models

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2011, Data Mining and Knowledge Discovery.

Discriminative Learning of Mixture of Bayesian Network Classifiers for Sequence Classification

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

On PyTorch Implementation of Density Estimators for von Mises-Fisher and Its Mixture

Minyoung Kim, 2021, ArXiv.

Learning Disentangled Factors from Paired Data in Cross-Modal Retrieval: An Implicit Identifiable VAE Approach

Vladimir Pavlovic, Minyoung Kim, Ricardo Guerrero, 2021, ACM Multimedia.

Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach

Minyoung Kim, V. Pavlovic, Pritish Sahu, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Discriminative Learning of Dynamical Systems for Motion Tracking

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

SwAMP: Swapped Assignment of Multi-Modal Pairs for Cross-Modal Retrieval pdf

Minyoung Kim, Minyoung Kim, 2021, AISTATS.

Recursive Inference for Variational Autoencoders pdf

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2020, NeurIPS.

FedHB: Hierarchical Bayesian Federated Learning

Timothy M. Hospedales, Minyoung Kim, 2023, ArXiv.

A maximum-likelihood and moment-matching density estimator for crowd-sourcing label prediction

Minyoung Kim, Minyoung Kim, 2017, Applied Intelligence.

Dual soft assignment clustering algorithm for human action video clustering

Minyoung Kim, Minyoung Kim, 2017, Comput. Vis. Image Underst..

Large-margin learning of Cox proportional hazard models for survival analysis

Minyoung Kim, 2018, Applied Intelligence.

Learning Disentangled Latent Factors from Paired Data in Cross-Modal Retrieval: An Implicit Identifiable VAE Approach pdf

Vladimir Pavlovic, Ricardo Guerrero, Minyoung Kim, 2020, ArXiv.

Discriminative Learning for Dynamic State Prediction

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Sequence Alignment by Regression Coding

Minyoung Kim, Minyoung Kim, 2011, IEEE Signal Processing Letters.

Reducing the Amortization Gap in Variational Autoencoders: A Bayesian Random Function Approach pdf

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2021, ArXiv.

Correlation-based incremental visual tracking

Minyoung Kim, Minyoung Kim, 2012, Pattern Recognit..

Multiple-concept feature generative models for multi-label image classification

Minyoung Kim, Minyoung Kim, 2015, Comput. Vis. Image Underst..

Variational Inference for Gaussian Process Models for Survival Analysis

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2018, UAI.

Simultaneous Kernel Learning and Label Imputation for Pattern Classification with Partially Labeled Data

Minyoung Kim, Minyoung Kim, 2017, Int. J. Fuzzy Log. Intell. Syst..

Gaussian Process Modeling of Approximate Inference Errors for Variational Autoencoders

Minyoung Kim, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Sparse discriminative region selection algorithm for face recognition

Minyoung Kim, 2015, Applied intelligence (Boston).

Discriminative models and dimensionality reduction for regression

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2008 .

Sparse large-margin nearest neighbor embedding via greedy dyad functional optimization

Minyoung Kim, Minyoung Kim, 2019, Applied Intelligence.

Document Summarization via Convex-Concave Programming

Minyoung Kim, Minyoung Kim, 2016, Int. J. Fuzzy Log. Intell. Syst..

Ordinal-Content VAE: Isolating Ordinal-Valued Content Factors in Deep Latent Variable Models pdf

Vladimir Pavlovic, Minyoung Kim, Minyoung Kim, 2020, 2020 IEEE International Conference on Data Mining (ICDM).