Changyou Chen

According to our database1, Changyou Chen authored at least 116 papers between 2008 and 2022.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2022
Fine-Grained Attention and Feature-Sharing Generative Adversarial Networks for Single Image Super-Resolution.
IEEE Trans. Multim., 2022

2021
A Generic Approach for Enhancing GANs by Regularized Latent Optimization.
CoRR, 2021

LAFITE: Towards Language-Free Training for Text-to-Image Generation.
CoRR, 2021

Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees.
CoRR, 2021

Perception Point: Identifying Critical Learning Periods in Speech for Bilingual Networks.
CoRR, 2021

MINIMAL: Mining Models for Data Free Universal Adversarial Triggers.
CoRR, 2021

AES Systems Are Both Overstable And Oversensitive: Explaining Why And Proposing Defenses.
CoRR, 2021

Learning High-Dimensional Distributions with Latent Neural Fokker-Planck Kernels.
CoRR, 2021

SDA: Improving Text Generation with Self Data Augmentation.
CoRR, 2021

Transformer-based Conditional Variational Autoencoder for Controllable Story Generation.
CoRR, 2021

Outline to Story: Fine-grained Controllable Story Generation from Cascaded Events.
CoRR, 2021

What all do audio transformer models hear? Probing Acoustic Representations for Language Delivery and its Structure.
CoRR, 2021

Unsupervised Hashing with Contrastive Information Bottleneck.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Meta-Learning with Neural Tangent Kernels.
Proceedings of the 9th International Conference on Learning Representations, 2021

MixKD: Towards Efficient Distillation of Large-scale Language Models.
Proceedings of the 9th International Conference on Learning Representations, 2021

Measurement of premixed propane combustion equivalence ratio based on flame image color and support vector machine.
Proceedings of the ICCDA 2021: The 5th International Conference on Compute and Data Analysis, 2021

LIFI: Towards Linguistically Informed Frame Interpolation.
Proceedings of the IEEE International Conference on Acoustics, 2021

Rethinking Sentiment Style Transfer.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

ReMP: Rectified Metric Propagation for Few-Shot Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Unpaired Image-to-Image Translation via Latent Energy Transport.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Towards Fair Federated Learning With Zero-Shot Data Augmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Speaker-Conditioned Hierarchical Modeling for Automated Speech Scoring.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
My Teacher Thinks The World Is Flat! Interpreting Automatic Essay Scoring Mechanism.
CoRR, 2020

Graph Neural Networks with Composite Kernels.
CoRR, 2020

Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition.
CoRR, 2020

Reward Constrained Interactive Recommendation with Natural Language Feedback.
CoRR, 2020

Discretized Bottleneck in VAE: Posterior-Collapse-Free Sequence-to-Sequence Learning.
CoRR, 2020

Decomposed Adversarial Learned Inference.
CoRR, 2020

Learning Manifold Implicitly via Explicit Heat-Kernel Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Bayesian Multi-type Mean Field Multi-agent Imitation Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Weakly-Supervised Brain Tumor Classification with Global Diagnosis Label.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Feature Quantization Improves GAN Training.
Proceedings of the 37th International Conference on Machine Learning, 2020

Variance Reduction in Stochastic Particle-Optimization Sampling.
Proceedings of the 37th International Conference on Machine Learning, 2020

Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Bayesian Meta Sampling for Fast Uncertainty Adaptation.
Proceedings of the 8th International Conference on Learning Representations, 2020

Semantic Matching via Optimal Partial Transport.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Structure-Aware Human-Action Generation.
Proceedings of the Computer Vision - ECCV 2020, 2020

GLIMA: Global and Local Time Series Imputation with Multi-directional Attention Learning.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Nested-Wasserstein Self-Imitation Learning for Sequence Generation.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Generative Semantic Hashing Enhanced via Boltzmann Machines.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Improving Adversarial Text Generation by Modeling the Distant Future.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Variational Adversarial Kernel Learned Imitation Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
KernelNet: A Data-Dependent Kernel Parameterization for Deep Generative Modeling.
CoRR, 2019

Fine-grained Attention and Feature-sharing Generative Adversarial Networks for Single Image Super-Resolution.
CoRR, 2019

On Norm-Agnostic Robustness of Adversarial Training.
CoRR, 2019

Topic-Guided Variational Autoencoders for Text Generation.
CoRR, 2019

Scalable Thompson Sampling via Optimal Transport.
CoRR, 2019

A convergence analysis for a class of practical variance-reduction stochastic gradient MCMC.
Sci. China Inf. Sci., 2019

Multi-Scale Residual Hierarchical Dense Networks for Single Image Super-Resolution.
IEEE Access, 2019

Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Certified Adversarial Robustness with Additive Noise.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Topic-Guided Variational Auto-Encoder for Text Generation.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Differentially Private Empirical Risk Minimization with Non-convex Loss Functions.
Proceedings of the 36th International Conference on Machine Learning, 2019

InverseNet: Solving Inverse Problems of Multimedia Data with Splitting Networks.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2019

Improving Sequence-to-Sequence Learning via Optimal Transport.
Proceedings of the 7th International Conference on Learning Representations, 2019

PointCloud Saliency Maps.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Implicit Deep Latent Variable Models for Text Generation.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Document Hashing with Mixture-Prior Generative Models.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Scalable Thompson Sampling via Optimal Transport.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

On Connecting Stochastic Gradient MCMC and Differential Privacy.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Adversarial Learning of a Sampler Based on an Unnormalized Distribution.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Distributionally Adversarial Attack.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Self-Adversarially Learned Bayesian Sampling.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Communication-Efficient Stochastic Gradient MCMC for Neural Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Learning Saliency Maps for Adversarial Point-Cloud Generation.
CoRR, 2018

Sequence Generation with Guider Network.
CoRR, 2018

Second-Order Adversarial Attack and Certifiable Robustness.
CoRR, 2018

Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory.
CoRR, 2018

A Unified Particle-Optimization Framework for Scalable Bayesian Sampling.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Holistic Brain Tumor Screening and Classification Based on DenseNet and Recurrent Neural Network.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

Deep Q-Learning for Dry Stacking Irregular Objects.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Policy Optimization as Wasserstein Gradient Flows.
Proceedings of the 35th International Conference on Machine Learning, 2018

Continuous-Time Flows for Efficient Inference and Density Estimation.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Structural Weight Uncertainty for Sequential Decision-Making.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Symmetric Variational Autoencoder and Connections to Adversarial Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Zero-Shot Learning via Class-Conditioned Deep Generative Models.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Towards Understanding Adversarial Learning for Joint Distribution Matching.
CoRR, 2017

ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Stochastic Gradient Monomial Gamma Sampler.
Proceedings of the 34th International Conference on Machine Learning, 2017

Learning Structured Weight Uncertainty in Bayesian Neural Networks.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016
Nonparametric Bayesian topic modelling with the hierarchical Pitman-Yor processes.
Int. J. Approx. Reason., 2016

Earliness-Aware Deep Convolutional Networks for Early Time Series Classification.
CoRR, 2016

Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling.
CoRR, 2016

Laplacian Hamiltonian Monte Carlo.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Deep Metric Learning with Data Summarization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Towards Unifying Hamiltonian Monte Carlo and Slice Sampling.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

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

Nonlinear Statistical Learning with Truncated Gaussian Graphical Models.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Differential Topic Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Scalable Deep Poisson Factor Analysis for Topic Modeling.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Bayesian Sampling Using Stochastic Gradient Thermostats.
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

2013
Dependent Normalized Random Measures.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Non-Parametric Kernel Learning with robust pairwise constraints.
Int. J. Mach. Learn. Cybern., 2012

Sequential latent Dirichlet allocation.
Knowl. Inf. Syst., 2012

Theory of Dependent Hierarchical Normalized Random Measures
CoRR, 2012

Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

2010
Low-Resolution Gait Recognition.
IEEE Trans. Syst. Man Cybern. Part B, 2010

Distance Approximating Dimension Reduction of Riemannian Manifolds.
IEEE Trans. Syst. Man Cybern. Part B, 2010

2009
Multilinear Tensor-Based Non-parametric Dimension Reduction for Gait Recognition.
Proceedings of the Advances in Biometrics, Third International Conference, 2009

2008
Low Resolution Gait Recognition with High Frequency Super Resolution.
Proceedings of the PRICAI 2008: Trends in Artificial Intelligence, 2008


  Loading...