Minyoung Kim

CoRR, May, 2025

Model Diffusion for Certifiable Few-shot Transfer Learning.

[BibT_eX]

[DOI]

Fady Rezk

Royson Lee

Henry Gouk

CoRR, February, 2025

FedP<sup>2</sup>EFT: Federated Learning to Personalize Parameter Efficient Fine-Tuning for Multilingual LLMs.

[BibT_eX]

[DOI]

Stylianos I. Venieris

CoRR, February, 2025

LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning.

[BibT_eX]

[DOI]

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

A Bayesian Approach to Data Point Selection.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

A Hierarchical Bayesian Model for Few-Shot Meta Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

BayesDLL: Bayesian Deep Learning Library.

[BibT_eX]

[DOI]

CoRR, 2023

A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning.

[BibT_eX]

[DOI]

CoRR, 2023

FedHB: Hierarchical Bayesian Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2023

FedL2P: Federated Learning to Personalize.

[BibT_eX]

[DOI]

Ferenc Huszar

Nicholas D. Lane

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

BayesTune: Bayesian Sparse Deep Model Fine-tuning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach.

[BibT_eX]

[DOI]

Da Li

Proceedings of the Eleventh International Conference on Learning Representations, 2023

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

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Fisher SAM: Information Geometry and Sharpness Aware Minimisation.

[BibT_eX]

[DOI]

Da Li

Shell Xu Hu

Proceedings of the International Conference on Machine Learning, 2022

Differentiable Expectation-Maximization for Set Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Gaussian Process Modeling of Approximate Inference Errors for Variational Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

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

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Variational Continual Proxy-Anchor for Deep Metric Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

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

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

Ricardo Guerrero

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

2020

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

[BibT_eX]

[DOI]

Ricardo Guerrero

CoRR, 2020

Recursive Inference for Variational Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019

Efficient Deep Gaussian Process Models for Variable-Sized Input.

[BibT_eX]

[DOI]

CoRR, 2019

Relevance Factor VAE: Learning and Identifying Disentangled Factors.

[BibT_eX]

[DOI]

CoRR, 2019

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

[BibT_eX]

[DOI]

Appl. Intell., 2019

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

[BibT_eX]

[DOI]

Appl. Intell., 2019

Efficient Deep Gaussian Process Models for Variable-Sized Inputs.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2019

Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

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

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

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

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

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

[BibT_eX]

[DOI]

Appl. Intell., 2018

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

[BibT_eX]

[DOI]

Appl. Intell., 2018

Variational Inference for Gaussian Process Models for Survival Analysis.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Mixtures of Conditional Random Fields for Improved Structured Output Prediction.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2017

Simultaneous Learning of Sentence Clustering and Class Prediction for Improved Document Classification.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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

Efficient histogram dictionary learning for text/image modeling and classification.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2017

Dual soft assignment clustering algorithm for human action video clustering.

[BibT_eX]

[DOI]

Comput. Vis. Image Underst., 2017

2016

Sparse conditional copula models for structured output regression.

[BibT_eX]

[DOI]

Pattern Recognit., 2016

Document Summarization via Convex-Concave Programming.

[BibT_eX]

[DOI]

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

Adaptive Bayesian Object Tracking with Histograms of Dense Local Image Descriptors.

[BibT_eX]

[DOI]

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

Robust Algorithms for Combining Multiple Term Weighting Vectors for Document Classification.

[BibT_eX]

[DOI]

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

Model-induced term-weighting schemes for text classification.

[BibT_eX]

[DOI]

Hyun Kyung Kim

Appl. Intell., 2016

Sparse inverse covariance learning of conditional Gaussian mixtures for multiple-output regression.

[BibT_eX]

[DOI]

Appl. Intell., 2016

2015

Greedy approaches to semi-supervised subspace learning.

[BibT_eX]

[DOI]

Pattern Recognit., 2015

Greedy ensemble learning of structured predictors for sequence tagging.

[BibT_eX]

[DOI]

Neurocomputing, 2015

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

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

Comput. Vis. Image Underst., 2015

Sparse discriminative region selection algorithm for face recognition.

[BibT_eX]

[DOI]

Appl. Intell., 2015

2014

Efficient Kernel Sparse Coding Via First-Order Smooth Optimization.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2014

Probabilistic Sequence Translation-Alignment Model for Time-Series Classification.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2014

Discriminative Training of Sequence Taggers via Local Feature Matching.

[BibT_eX]

[DOI]

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

Greedy Learning of Sparse Eigenfaces for Face Recognition and Tracking.

[BibT_eX]

[DOI]

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

Robust Video-Based Barcode Recognition via Online Sequential Filtering.

[BibT_eX]

[DOI]

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

Multiple instance learning via Gaussian processes.

[BibT_eX]

[DOI]

Fernando De la Torre

Data Min. Knowl. Discov., 2014

Conditional ordinal random fields for structured ordinal-valued label prediction.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2014

2013

Conditional Alignment Random Fields for Multiple Motion Sequence Alignment.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2013

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

[BibT_eX]

[DOI]

Neurocomputing, 2013

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

[BibT_eX]

[DOI]

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

Accelerated max-margin multiple kernel learning.

[BibT_eX]

[DOI]

Appl. Intell., 2013

2012

Time-Series Dimensionality Reduction via Granger Causality.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2012

Correlation-based incremental visual tracking.

[BibT_eX]

[DOI]

Pattern Recognit., 2012

2011

Sequence Alignment by Regression Coding.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2011

Discriminative semi-supervised learning of dynamical systems for motion estimation.

[BibT_eX]

[DOI]

Pattern Recognit., 2011

Central Subspace Dimensionality Reduction Using Covariance Operators.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2011

Sequence classification via large margin hidden Markov models.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2011

2010

Large margin cost-sensitive learning of conditional random fields.

[BibT_eX]

[DOI]

Pattern Recognit., 2010

Hidden Conditional Ordinal Random Fields for Sequence Classification.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Gaussian Processes Multiple Instance Learning.

[BibT_eX]

[DOI]

Fernando De la Torre

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Local Minima Embedding.

[BibT_eX]

[DOI]

Fernando De la Torre

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

A Real-Time System for Head Tracking and Pose Estimation.

[BibT_eX]

[DOI]

Proceedings of the Trends and Topics in Computer Vision, 2010

Structured Output Ordinal Regression for Dynamic Facial Emotion Intensity Prediction.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision, 2010

2009

Discriminative Learning for Dynamic State Prediction.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2009

Covariance Operator Based Dimensionality Reduction with Extension to Semi-Supervised Settings.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

2008

Dimensionality reduction using covariance operator inverse regression.

[BibT_eX]

[DOI]

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

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

[BibT_eX]

[DOI]

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2007

A recursive method for discriminative mixture learning.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2007

Conditional State Space Models for Discriminative Motion Estimation.

[BibT_eX]

[DOI]

Proceedings of the IEEE 11th International Conference on Computer Vision, 2007

Discriminative Learning of Dynamical Systems for Motion Tracking.

[BibT_eX]

[DOI]

Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007

2006

Discriminative Learning of Mixture of Bayesian Network Classifiers for Sequence Classification.

[BibT_eX]

[DOI]