Mingyuan Zhou

Orcid: 0000-0002-4253-2780

According to our database1, Mingyuan Zhou authored at least 198 papers between 2008 and 2024.

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Bibliography

2024
Self-Supervised Generative-Contrastive Learning of Multi-Modal Euclidean Input for 3D Shape Latent Representations: A Dynamic Switching Approach.
IEEE Trans. Multim., 2024

Hierarchical Topic-Aware Contextualized Transformers.
IEEE ACM Trans. Audio Speech Lang. Process., 2024

Polarimetric Helmholtz Stereopsis.
IEEE Trans. Pattern Anal. Mach. Intell., 2024

One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation.
CoRR, 2024

Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step.
CoRR, 2024

Parameter estimation of structural dynamics with neural operators enabled surrogate modeling.
CoRR, 2024

Scalable Weibull Graph Attention Autoencoder for Modeling Document Networks.
CoRR, 2024

Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models.
CoRR, 2024

Disentangled Generative Graph Representation Learning.
CoRR, 2024

Openstory++: A Large-scale Dataset and Benchmark for Instance-aware Open-domain Visual Storytelling.
CoRR, 2024

A Non-negative VAE:the Generalized Gamma Belief Network.
CoRR, 2024

Contrastive Factor Analysis.
CoRR, 2024

Advancing Graph Generation through Beta Diffusion.
CoRR, 2024

Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization.
CoRR, 2024

Diffusion Boosted Trees.
CoRR, 2024

Long and Short Guidance in Score identity Distillation for One-Step Text-to-Image Generation.
CoRR, 2024

Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model Alignment.
CoRR, 2024

Diffusion Policies creating a Trust Region for Offline Reinforcement Learning.
CoRR, 2024

Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization.
CoRR, 2024

Relative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts.
CoRR, 2024

Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Switchable Decision: Dynamic Neural Generation Networks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Dense Reward View on Aligning Text-to-Image Diffusion with Preference.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Long-tailed Diffusion Models with Oriented Calibration.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

UltrAvatar: A Realistic Animatable 3D Avatar Diffusion Model with Authenticity Guided Textures.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

OpenStory: A Large-Scale Open-Domain Dataset for Subject-Driven Visual Storytelling.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

OmniMotionGPT: Animal Motion Generation with Limited Data.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Improving Unsupervised Hierarchical Representation With Reinforcement Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Learning Hierarchical Document Graphs From Multilevel Sentence Relations.
IEEE Trans. Neural Networks Learn. Syst., August, 2023

Generative Text Convolutional Neural Network for Hierarchical Document Representation Learning.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Contrastive Attraction and Contrastive Repulsion for Representation Learning.
Trans. Mach. Learn. Res., 2023

Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-Varying Covariates.
J. Mach. Learn. Res., 2023

Improving In-Context Learning in Diffusion Models with Visual Context-Modulated Prompts.
CoRR, 2023

AutoML-GPT: Automatic Machine Learning with GPT.
CoRR, 2023

Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond.
CoRR, 2023

Patch-Token Aligned Bayesian Prompt Learning for Vision-Language Models.
CoRR, 2023

A Prototype-Oriented Clustering for Domain Shift with Source Privacy.
CoRR, 2023

Generative-Contrastive Learning for Self-Supervised Latent Representations of 3D Shapes from Multi-Modal Euclidean Input.
CoRR, 2023

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

Preference-grounded Token-level Guidance for Language Model Fine-tuning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

In-Context Learning Unlocked for Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

POUF: Prompt-Oriented Unsupervised Fine-tuning for Large Pre-trained Models.
Proceedings of the International Conference on Machine Learning, 2023

Prototype-oriented unsupervised anomaly detection for multivariate time series.
Proceedings of the International Conference on Machine Learning, 2023

Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process.
Proceedings of the International Conference on Machine Learning, 2023

Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling.
Proceedings of the International Conference on Machine Learning, 2023

Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Diffusion-GAN: Training GANs with Diffusion.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

DR2: Diffusion-Based Robust Degradation Remover for Blind Face Restoration.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Class-Balancing Diffusion Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Uncertainty-aware Unsupervised Video Hashing.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Probabilistic Conformal Prediction Using Conditional Random Samples.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Infinite Switching Dynamic Probabilistic Network With Bayesian Nonparametric Learning.
IEEE Trans. Signal Process., 2022

Multimodal Weibull Variational Autoencoder for Jointly Modeling Image-Text Data.
IEEE Trans. Cybern., 2022

Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning.
Int. J. Comput. Vis., 2022

Ordinal Graph Gamma Belief Network for Social Recommender Systems.
CoRR, 2022

A Regularized Implicit Policy for Offline Reinforcement Learning.
CoRR, 2022

Truncated Diffusion Probabilistic Models.
CoRR, 2022

Mixing and Shifting: Exploiting Global and Local Dependencies in Vision MLPs.
CoRR, 2022

Attention-Based Deep Bayesian Counting For AI-Augmented Agriculture.
Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems, 2022

A Unified Framework for Alternating Offline Model Training and Policy Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Alleviating "Posterior Collapse" in Deep Topic Models via Policy Gradient.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Variational Edge Partition Model for Supervised Graph Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CARD: Classification and Regression Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Knowledge-Aware Bayesian Deep Topic Model.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

ALLSH: Active Learning Guided by Local Sensitivity and Hardness.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022

Bayesian Deep Embedding Topic Meta-Learner.
Proceedings of the International Conference on Machine Learning, 2022

Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection.
Proceedings of the International Conference on Machine Learning, 2022

Learning Prototype-oriented Set Representations for Meta-Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta Discovery: Learning to Discover Novel Classes given Very Limited Data.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Deep Autoencoding Topic Model With Scalable Hybrid Bayesian Inference.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Structure From Motion on XSlit Cameras.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Gradient estimation of information measures in deep learning.
Knowl. Based Syst., 2021

Bayesian Graph Contrastive Learning.
CoRR, 2021

Contrastive Conditional Transport for Representation Learning.
CoRR, 2021

Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Alignment Attention by Matching Key and Query Distributions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Probabilistic Margins for Instance Reweighting in Adversarial Training.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Prototype-Oriented Framework for Unsupervised Domain Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

TopicNet: Semantic Graph-Guided Topic Discovery.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Convex Polytope Trees and its Application to VAE.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bayesian Attention Belief Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network.
Proceedings of the 38th International Conference on Machine Learning, 2021

ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables.
Proceedings of the 38th International Conference on Machine Learning, 2021

Contextual Dropout: An Efficient Sample-Dependent Dropout Module.
Proceedings of the 9th International Conference on Learning Representations, 2021

Polarimetric Helmholtz Stereopsis.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Adversarially Adaptive Normalization for Single Domain Generalization.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Partition-Guided GANs.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Hyperbolic graph embedding with enhanced semi-implicit variational inference.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Graph Gamma Process Linear Dynamical Systems.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

EnsLM: Ensemble Language Model for Data Diversity by Semantic Clustering.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Variational Temporal Deep Generative Model for Radar HRRP Target Recognition.
IEEE Trans. Signal Process., 2020

Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Semi-supervised learning using adversarial training with good and bad samples.
Mach. Vis. Appl., 2020

ACT: Asymptotic Conditional Transport.
CoRR, 2020

Self-supervised Pre-training with Hard Examples Improves Visual Representations.
CoRR, 2020

Convex Polytope Trees.
CoRR, 2020

MCMC-Interactive Variational Inference.
CoRR, 2020

Graph Gamma Process Generalized Linear Dynamical Systems.
CoRR, 2020

Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Implicit Distributional Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

Bidirectional Convolutional Poisson Gamma Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Switching Poisson Gamma Dynamical Systems.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Thompson Sampling via Local Uncertainty.
Proceedings of the 37th International Conference on Machine Learning, 2020

Bayesian Graph Neural Networks with Adaptive Connection Sampling.
Proceedings of the 37th International Conference on Machine Learning, 2020

Recurrent Hierarchical Topic-Guided RNN for Language Generation.
Proceedings of the 37th International Conference on Machine Learning, 2020

Meta-Learning without Memorization.
Proceedings of the 8th International Conference on Learning Representations, 2020

Mutual Information Gradient Estimation for Representation Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation.
Proceedings of the 8th International Conference on Learning Representations, 2020

Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling.
Proceedings of the 8th International Conference on Learning Representations, 2020

3D Face Reconstruction using Color Photometric Stereo with Uncalibrated Near Point Lights.
Proceedings of the 2020 IEEE International Conference on Computational Photography, 2020

Semi-Implicit Stochastic Recurrent Neural Networks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Arsm Gradient Estimator for Supervised Learning to Rank.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Friendly Topic Assistant for Transformer Based Abstractive Summarization.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Variational Autoencoders for Sparse and Overdispersed Discrete Data.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Discrete Action On-Policy Learning with Action-Value Critic.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Learning Dynamic Hierarchical Topic Graph with Graph Convolutional Network for Document Classification.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Learnable Bernoulli Dropout for Bayesian Deep Learning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Content Aware Image Pre-Compensation.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Recurrent Hierarchical Topic-Guided Neural Language Models.
CoRR, 2019

Semi-Implicit Generative Model.
CoRR, 2019

Variational Hetero-Encoder Randomized Generative Adversarial Networks for Joint Image-Text Modeling.
CoRR, 2019

Variational Autoencoders for Sparse and Overdispersed Discrete Data.
CoRR, 2019

Non-Lambertian Surface Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field.
CoRR, 2019

Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy.
CoRR, 2019

Poisson-Randomized Gamma Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Semi-Implicit Graph Variational Auto-Encoders.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Variational Graph Recurrent Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables.
Proceedings of the 36th International Conference on Machine Learning, 2019

Convolutional Poisson Gamma Belief Network.
Proceedings of the 36th International Conference on Machine Learning, 2019

Locally Private Bayesian Inference for Count Models.
Proceedings of the 36th International Conference on Machine Learning, 2019

ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Deep Topic Models for Multi-label Learning.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
ARM: Augment-REINFORCE-Merge Gradient for Discrete Latent Variable Models.
CoRR, 2018

Locally Private Bayesian Inference for Count Models.
CoRR, 2018

Bayesian negative binomial regression for differential expression with confounding factors.
Bioinform., 2018

Covariate-dependent negative binomial factor analysis of RNA sequencing data.
Bioinform., 2018

Parsimonious Bayesian deep networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Dirichlet belief networks for topic structure learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Masking: A New Perspective of Noisy Supervision.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Poisson gamma dynamical systems.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Dual Markov Chain Topic Model for Dynamic Environments.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Inter and Intra Topic Structure Learning with Word Embeddings.
Proceedings of the 35th International Conference on Machine Learning, 2018

Semi-Implicit Variational Inference.
Proceedings of the 35th International Conference on Machine Learning, 2018

WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling.
Proceedings of the 6th International Conference on Learning Representations, 2018

Nonparametric Bayesian sparse graph linear dynamical systems.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Multimodal Poisson Gamma Belief Network.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression.
J. Mach. Learn. Res., 2017

Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Augmentable Gamma Belief Networks.
J. Mach. Learn. Res., 2016

Poisson-Gamma dynamical systems.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Rotational Crossed-Slit Light Fields.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Negative Binomial Process Count and Mixture Modeling.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

A Bayesian Nonparametric Approach to Image Super-Resolution.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Gamma Process Poisson Factorization for Joint Modeling of Network and Documents.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

The Poisson Gamma Belief Network.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Nonparametric Bayesian matrix factorization for assortative networks.
Proceedings of the 23rd European Signal Processing Conference, 2015

Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Hybrid sensing face detection and recognition.
Proceedings of the 2015 IEEE Applied Imagery Pattern Recognition Workshop, 2015

2014
Multichannel Electrophysiological Spike Sorting via Joint Dictionary Learning and Mixture Modeling.
IEEE Trans. Biomed. Eng., 2014

Beta-Negative Binomial Process and Exchangeable Random Partitions for Mixed-Membership Modeling.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2012
Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images.
IEEE Trans. Image Process., 2012

Dictionary Learning for Noisy and Incomplete Hyperspectral Images.
SIAM J. Imaging Sci., 2012

Beta-Negative Binomial Process and Poisson Factor Analysis.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Nested Dictionary Learning for Hierarchical Organization of Imagery and Text.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Augment-and-Conquer Negative Binomial Processes.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

The contextual focused topic model.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Lognormal and Gamma Mixed Negative Binomial Regression.
Proceedings of the 29th International Conference on Machine Learning, 2012

Online Bayesian dictionary learning for large datasets.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

A GPU-based implementation of an enhanced GEP algorithm.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

2011
Dependent Hierarchical Beta Process for Image Interpolation and Denoising.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

On the Integration of Topic Modeling and Dictionary Learning.
Proceedings of the 28th International Conference on Machine Learning, 2011

Covariate-dependent dictionary learning and sparse coding.
Proceedings of the IEEE International Conference on Acoustics, 2011

Joint dictionary learning and topic modeling for image clustering.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
IBM Research TRECVID-2010 Video Copy Detection and Multimedia Event Detection System.
Proceedings of the TRECVID 2010 workshop participants notebook papers, 2010

Nonparametric image interpolation and dictionary learning using spatially-dependent Dirichlet and beta process priors.
Proceedings of the International Conference on Image Processing, 2010

2009
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008
On the relationship of non-parametric methods for coherence function estimation.
Signal Process., 2008


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