Jun Zhu

According to our database1, Jun Zhu authored at least 137 papers between 2005 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2019
Scalable Training of Inference Networks for Gaussian-Process Models.
Proceedings of the 36th International Conference on Machine Learning, 2019

Understanding and Accelerating Particle-Based Variational Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019

Understanding MCMC Dynamics as Flows on the Wasserstein Space.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Visual Diagnosis of Tree Boosting Methods.
IEEE Trans. Vis. Comput. Graph., 2018

Analyzing the Training Processes of Deep Generative Models.
IEEE Trans. Vis. Comput. Graph., 2018

Learning Deep Generative Models With Doubly Stochastic Gradient MCMC.
IEEE Trans. Neural Netw. Learning Syst., 2018

Scalable Training of Hierarchical Topic Models.
PVLDB, 2018

Spectral Learning for Supervised Topic Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Max-Margin Deep Generative Models for (Semi-)Supervised Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Dropout training for SVMs with data augmentation.
Frontiers Comput. Sci., 2018

Towards Robust Detection of Adversarial Examples.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Semi-crowdsourced Clustering with Deep Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Graphical Generative Adversarial Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Probabilistic Machine Learning: Models, Algorithms and a Programming Library.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Learning to Write Stylized Chinese Characters by Reading a Handful of Examples.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Message Passing Stein Variational Gradient Descent.
Proceedings of the 35th International Conference on Machine Learning, 2018

Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors.
Proceedings of the 35th International Conference on Machine Learning, 2018

A Spectral Approach to Gradient Estimation for Implicit Distributions.
Proceedings of the 35th International Conference on Machine Learning, 2018

Max-Mahalanobis Linear Discriminant Analysis Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

Adversarial Attack on Graph Structured Data.
Proceedings of the 35th International Conference on Machine Learning, 2018

Stochastic Training of Graph Convolutional Networks with Variance Reduction.
Proceedings of the 35th International Conference on Machine Learning, 2018

Essay-Anchor Attentive Multi-Modal Bilinear Pooling for Textbook Question Answering.
Proceedings of the 2018 IEEE International Conference on Multimedia and Expo, 2018

Kernel Implicit Variational Inference.
Proceedings of the 6th International Conference on Learning Representations, 2018

Smooth Neighbors on Teacher Graphs for Semi-Supervised Learning.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Defense Against Adversarial Attacks Using High-Level Representation Guided Denoiser.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Textbook Question Answering Under Instructor Guidance With Memory Networks.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Boosting Adversarial Attacks With Momentum.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Understanding Human Behaviors in Crowds by Imitating the Decision-Making Process.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Towards Training Probabilistic Topic Models on Neuromorphic Multi-Chip Systems.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Selective Verification Strategy for Learning From Crowds.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Riemannian Stein Variational Gradient Descent for Bayesian Inference.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Collaborative Filtering With User-Item Co-Autoregressive Models.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Towards better analysis of machine learning models: A visual analytics perspective.
Visual Informatics, 2017

Towards Better Analysis of Deep Convolutional Neural Networks.
IEEE Trans. Vis. Comput. Graph., 2017

Special Issue on Biomedical Big Data: Understanding, Learning and Applications.
IEEE Trans. Big Data, 2017

PSDVec: A toolbox for incremental and scalable word embedding.
Neurocomputing, 2017

Fast sampling methods for Bayesian max-margin models.
Expert Syst. Appl., 2017

Triple Generative Adversarial Nets.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Structured Generative Adversarial Networks.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Population Matching Discrepancy and Applications in Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Forecast the Plausible Paths in Crowd Scenes.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Distributed Accelerated Proximal Coordinate Gradient Methods.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Improving Learning-from-Crowds through Expert Validation.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Semi-supervised Max-margin Topic Model with Manifold Posterior Regularization.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Identify the Nash Equilibrium in Static Games with Random Payoffs.
Proceedings of the 34th International Conference on Machine Learning, 2017

Improving Interpretability of Deep Neural Networks with Semantic Information.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs.
Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems, 2017

Learning Attributes from the Crowdsourced Relative Labels.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
TopicPanorama: A Full Picture of Relevant Topics.
IEEE Trans. Vis. Comput. Graph., 2016

Interactive Cell Segmentation Based on Active and Semi-Supervised Learning.
IEEE Trans. Med. Imaging, 2016

WarpLDA: a Cache Efficient O(1) Algorithm for Latent Dirichlet Allocation.
PVLDB, 2016

BitHash: An efficient bitwise Locality Sensitive Hashing method with applications.
Knowl.-Based Syst., 2016

Scaling up Dynamic Topic Models.
Proceedings of the 25th International Conference on World Wide Web, 2016

Kernel Bayesian Inference with Posterior Regularization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Conditional Generative Moment-Matching Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Stochastic Gradient Geodesic MCMC Methods.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Distributing the Stochastic Gradient Sampler for Large-Scale LDA.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Crowd Scene Understanding with Coherent Recurrent Neural Networks.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Diversity-Promoting Bayesian Learning of Latent Variable Models.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning to Generate with Memory.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Efficient and Robust Semi-supervised Learning Over a Sparse-Regularized Graph.
Proceedings of the Computer Vision - ECCV 2016, 2016

Neuron Segmentation Based on CNN with Semi-Supervised Regularization.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016

Segment-Level Sequence Modeling using Gated Recursive Semi-Markov Conditional Random Fields.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Discriminative Deep Random Walk for Network Classification.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Generative Topic Embedding: a Continuous Representation of Documents.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Bayesian Matrix Completion via Adaptive Relaxed Spectral Regularization.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Jointly Modeling Topics and Intents with Global Order Structure.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Discriminative Relational Topic Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Crowd Fraud Detection in Internet Advertising.
Proceedings of the 24th International Conference on World Wide Web, 2015

Uncovering the Latent Structures of Crowd Labeling.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

Max-Margin Majority Voting for Learning from Crowds.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Building Memory with Concept Learning Capabilities from Large-Scale Knowledge Bases.
Proceedings of the NIPS Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches co-located with the 29th Annual Conference on Neural Information Processing Systems (NIPS 2015), 2015

Max-Margin Deep Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Polyphonic Music Modelling with LSTM-RTRBM.
Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, MM '15, Brisbane, Australia, October 26, 2015

Adaptive Dropout Rates for Learning with Corrupted Features.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Modelling High-Dimensional Sequences with LSTM-RTRBM: Application to Polyphonic Music Generation.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics.
Proceedings of the 32nd International Conference on Machine Learning, 2015

A Generative Word Embedding Model and its Low Rank Positive Semidefinite Solution.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015

Large Scale Sentiment Analysis with Locality Sensitive BitHash.
Proceedings of the Information Retrieval Technology, 2015

2014
Discriminative Training of Mixed Membership Models.
Proceedings of the Handbook of Mixed Membership Models and Their Applications., 2014

Learning Harmonium Models With Infinite Latent Features.
IEEE Trans. Neural Netw. Learning Syst., 2014

Bayesian inference with posterior regularization and applications to infinite latent SVMs.
J. Mach. Learn. Res., 2014

Gibbs max-margin topic models with data augmentation.
J. Mach. Learn. Res., 2014

Nonparametric bayesian upstream supervised multi-modal topic models.
Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Distributed Bayesian Posterior Sampling via Moment Sharing.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Spectral Methods for Supervised Topic Models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Robust Bayesian Max-Margin Clustering.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Max-margin latent feature relational models for entity-attribute networks.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Max-Margin Infinite Hidden Markov Models.
Proceedings of the 31th International Conference on Machine Learning, 2014

Online Bayesian Passive-Aggressive Learning.
Proceedings of the 31th International Conference on Machine Learning, 2014

Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models.
Proceedings of the 31th International Conference on Machine Learning, 2014

Bayesian Max-margin Multi-Task Learning with Data Augmentation.
Proceedings of the 31th International Conference on Machine Learning, 2014

Small-Variance Asymptotics for Dirichlet Process Mixtures of SVMs.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Dropout Training for Support Vector Machines.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Learning a Contextual Multi-Thread Model for Movie/TV Scene Segmentation.
IEEE Trans. Multimedia, 2013

Sparse online topic models.
Proceedings of the 22nd International World Wide Web Conference, 2013

Sparse Relational Topic Models for Document Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Scalable Inference for Logistic-Normal Topic Models.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Scalable inference in max-margin topic models.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Generalized Relational Topic Models with Data Augmentation.
Proceedings of the IJCAI 2013, 2013

Gibbs Max-Margin Topic Models with Fast Sampling Algorithms.
Proceedings of the 30th International Conference on Machine Learning, 2013

Fast Max-Margin Matrix Factorization with Data Augmentation.
Proceedings of the 30th International Conference on Machine Learning, 2013

Discriminative infinite latent feature models.
Proceedings of the 2013 IEEE China Summit and International Conference on Signal and Information Processing, 2013

Improved Bayesian Logistic Supervised Topic Models with Data Augmentation.
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, 2013

2012
Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

MedLDA: maximum margin supervised topic models.
J. Mach. Learn. Res., 2012

Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction.
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

Monte Carlo Methods for Maximum Margin Supervised Topic Models.
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

Learning from crowds in the presence of schools of thought.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Max-Margin Nonparametric Latent Feature Models for Link Prediction.
Proceedings of the 29th International Conference on Machine Learning, 2012

Multi-Level Structured Image Coding on High-Dimensional Image Representation.
Proceedings of the Computer Vision, 2012

2011
Sparse Topical Coding.
Proceedings of the UAI 2011, 2011

Infinite Latent SVM for Classification and Multi-task Learning.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Conditional topical coding: an efficient topic model conditioned on rich features.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Large Margin Learning of Upstream Scene Understanding Models.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Adaptive Multi-Task Lasso: with Application to eQTL Detection.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Efficient Relational Learning with Hidden Variable Detection.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Predictive Subspace Learning for Multi-view Data: a Large Margin Approach.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Grafting-light: fast, incremental feature selection and structure learning of Markov random fields.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

Conditional Topic Random Fields.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009
Statistical Web Object Extraction.
Proceedings of the Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes), 2009

Maximum Entropy Discrimination Markov Networks.
J. Mach. Learn. Res., 2009

StatSnowball: a statistical approach to extracting entity relationships.
Proceedings of the 18th International Conference on World Wide Web, 2009

Incorporating site-level knowledge to extract structured data from web forums.
Proceedings of the 18th International Conference on World Wide Web, 2009

Primal sparse Max-margin Markov networks.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

User grouping behavior in online forums.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

On primal and dual sparsity of Markov networks.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

MedLDA: maximum margin supervised topic models for regression and classification.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction.
J. Mach. Learn. Res., 2008

Partially Observed Maximum Entropy Discrimination Markov Networks.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Laplace maximum margin Markov networks.
Proceedings of the Machine Learning, 2008

2007
Webpage understanding: an integrated approach.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Dynamic hierarchical Markov random fields and their application to web data extraction.
Proceedings of the Machine Learning, 2007

2006
Simultaneous record detection and attribute labeling in web data extraction.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

2005
2D Conditional Random Fields for Web information extraction.
Proceedings of the Machine Learning, 2005


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