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Hung Bui

26 papers · 2008–2022 · 9 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (6) 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (14) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (11) πŸ—ΊοΈ Taxonomy Completionist (16) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ† Grand Slam 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ“ˆ Trend Setter ⚑ Prolific Year (9) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (51) πŸ’Ž Century Club (26) πŸ”₯ Unstoppable (7)

Conferences

ICML (7) IJCAI (5) ICLR (4) NIPS (4) AISTATS (2) AAAI (1) CVPR (1) JMLR (1) NAACL (1)

Top co-authors

Dinh Phung (10) nhαΊ­t Hα»“ (8) Trung Le (7) Rui Shu (6) Tung Pham (5) Stefano Ermon (4) Khai Nguyen (4) Mohammad Ghavamzadeh (3) Tu Dinh Nguyen (3) Quan Hoang (2)

Keywords

optimal transport (4) wasserstein distance (3) latent space (3) variational inference (3) domain adaptation (3) generative adversarial network (3) variational autoencoder (2) transfer learning (2) representation learning (2) hidden markov model (2) sinkhorn algorithm (2) bayesian nonparametric (2) model-based reinforcement learning (2) computational complexity (2) optimal control (2) probability measure (2) dynamical system (2) gibbs sampling (2) entropic regularization (2) reparameterization trick (2)

Papers

On Transportation of Mini-batches: A Hierarchical Approach ICML 2022
Temporal Predictive Coding For Model-Based Planning In Latent Space ICML 2021
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources NIPS 2021
Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior AAAI 2021
Structured Dropout Variational Inference for Bayesian Neural Networks NIPS 2021
On Robust Optimal Transport: Computational Complexity and Barycenter Computation NIPS 2021
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein ICLR 2021
Distributional Sliced-Wasserstein and Applications to Generative Modeling ICLR 2021
On efficient multilevel Clustering via Wasserstein distances JMLR 2021
LAMDA: Label Matching Deep Domain Adaptation ICML 2021
Vec2Face: Unveil Human Faces From Their Blackbox Features in Face Recognition CVPR 2020
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems ICML 2020
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control ICLR 2020
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm ICML 2020
Predictive Coding for Locally-Linear Control ICML 2020
Training Variational Autoencoders with Buffered Stochastic Variational Inference AISTATS 2019
Learning Generative Adversarial Networks from Multiple Data Sources IJCAI 2019
Three-Player Wasserstein GAN via Amortised Duality IJCAI 2019
The Context-Dependent Additive Recurrent Neural Net NAACL 2018
Robust Locally-Linear Controllable Embedding AISTATS 2018
A DIRT-T Approach to Unsupervised Domain Adaptation ICLR 2018
Discriminative Bayesian Nonparametric Clustering IJCAI 2017
Large-scale Online Kernel Learning with Random Feature Reparameterization IJCAI 2017
Practical Linear Models for Large-Scale One-Class Collaborative Filtering IJCAI 2016
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts ICML 2014
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data NIPS 2008