Jun Zhu

Affiliations:
  • Tsinghua University, State Key Laboratory of Intelligent Technology and Systems, TNList, Beijing, China
  • Tsinghua University, Department of Computer Science and Technology, Beijing, China
  • Carnegie Mellon University, Machine Learning Department, Pittsburgh, PA, USA (former)


According to our database1, Jun Zhu authored at least 390 papers between 2005 and 2024.

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Bibliography

2024
Probabilistic Neural-Symbolic Models With Inductive Posterior Constraints.
IEEE Trans. Neural Networks Learn. Syst., February, 2024

2023
Incorporating neuro-inspired adaptability for continual learning in artificial intelligence.
Nat. Mac. Intell., December, 2023

Heterogeneous multi-task Gaussian Cox processes.
Mach. Learn., December, 2023

To make yourself invisible with Adversarial Semantic Contours.
Comput. Vis. Image Underst., April, 2023

Toward the third generation artificial intelligence.
Sci. China Inf. Sci., February, 2023

Batch virtual adversarial training for graph convolutional networks.
AI Open, January, 2023

A semismooth Newton based augmented Lagrangian method for nonsmooth optimization on matrix manifolds.
Math. Program., 2023

Schrodinger Bridges Beat Diffusion Models on Text-to-Speech Synthesis.
CoRR, 2023

LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents.
CoRR, 2023

InstructPix2NeRF: Instructed 3D Portrait Editing from a Single Image.
CoRR, 2023

DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics.
CoRR, 2023

How Robust is Google's Bard to Adversarial Image Attacks?
CoRR, 2023

PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.
CoRR, 2023

ControlVideo: Adding Conditional Control for One Shot Text-to-Video Editing.
CoRR, 2023

Robust Classification via a Single Diffusion Model.
CoRR, 2023

Learning Sample Difficulty from Pre-trained Models for Reliable Prediction.
CoRR, 2023

Detection Transformer with Stable Matching.
CoRR, 2023

A Closer Look at Parameter-Efficient Tuning in Diffusion Models.
CoRR, 2023

Rethinking Model Ensemble in Transfer-based Adversarial Attacks.
CoRR, 2023

Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.
CoRR, 2023

Reward Informed Dreamer for Task Generalization in Reinforcement Learning.
CoRR, 2023

A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking.
CoRR, 2023

Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels.
CoRR, 2023

Revisiting Discriminative vs. Generative Classifiers: Theory and Implications.
CoRR, 2023

A Comprehensive Survey of Continual Learning: Theory, Method and Application.
CoRR, 2023

A constrained Bayesian approach to out-of-distribution prediction.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Accelerated Model Training via Bayesian Data Selection.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

On the Reuse Bias in Off-Policy Reinforcement Learning.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs.
Proceedings of the International Conference on Machine Learning, 2023

MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data.
Proceedings of the International Conference on Machine Learning, 2023

GNOT: A General Neural Operator Transformer for Operator Learning.
Proceedings of the International Conference on Machine Learning, 2023

One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale.
Proceedings of the International Conference on Machine Learning, 2023

Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Equivariant Energy-Guided SDE for Inverse Molecular Design.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

PREIM3D: 3D Consistent Precise Image Attribute Editing from a Single Image.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

All are Worth Words: A ViT Backbone for Diffusion Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Diagnosing Ensemble Few-Shot Classifiers.
IEEE Trans. Vis. Comput. Graph., 2022

Triple-Memory Networks: A Brain-Inspired Method for Continual Learning.
IEEE Trans. Neural Networks Learn. Syst., 2022

Towards generalizable detection of face forgery via self-guided model-agnostic learning.
Pattern Recognit. Lett., 2022

Deep reinforcement learning with credit assignment for combinatorial optimization.
Pattern Recognit., 2022

Loss function search for person re-identification.
Pattern Recognit., 2022

Triple Generative Adversarial Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Query-Efficient Black-Box Adversarial Attacks Guided by a Transfer-Based Prior.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Tianshou: A Highly Modularized Deep Reinforcement Learning Library.
J. Mach. Learn. Res., 2022

Amplification trojan network: Attack deep neural networks by amplifying their inherent weakness.
Neurocomputing, 2022

Why Are Conditional Generative Models Better Than Unconditional Ones?
CoRR, 2022

Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications.
CoRR, 2022

DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models.
CoRR, 2022

Improving transferability of 3D adversarial attacks with scale and shear transformations.
CoRR, 2022

Model-based Reinforcement Learning with a Hamiltonian Canonical ODE Network.
CoRR, 2022

Spectral Representation Learning for Conditional Moment Models.
CoRR, 2022

Neural Eigenfunctions Are Structured Representation Learners.
CoRR, 2022

All are Worth Words: a ViT Backbone for Score-based Diffusion Models.
CoRR, 2022

Consistent Attack: Universal Adversarial Perturbation on Embodied Vision Navigation.
CoRR, 2022

Fast Instrument Learning with Faster Rates.
CoRR, 2022

Deep Ensemble as a Gaussian Process Approximate Posterior.
CoRR, 2022

Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognition.
CoRR, 2022

AutoDA: Automated Decision-based Iterative Adversarial Attacks.
Proceedings of the 31st USENIX Security Symposium, 2022

Fast Instrument Learning with Faster Rates.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Isometric 3D Adversarial Examples in the Physical World.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Accelerated Linearized Laplace Approximation for Bayesian Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Confidence-based Reliable Learning under Dual Noises.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The More, The Better? Active Silencing of Non-Positive Transfer for Efficient Multi-Domain Few-Shot Classification.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Fast Lossless Neural Compression with Integer-Only Discrete Flows.
Proceedings of the International Conference on Machine Learning, 2022

Robustness and Accuracy Could Be Reconcilable by (Proper) Definition.
Proceedings of the International Conference on Machine Learning, 2022

Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching.
Proceedings of the International Conference on Machine Learning, 2022

GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing.
Proceedings of the International Conference on Machine Learning, 2022

NeuralEF: Deconstructing Kernels by Deep Neural Networks.
Proceedings of the International Conference on Machine Learning, 2022

Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models.
Proceedings of the International Conference on Machine Learning, 2022

Memory Replay with Data Compression for Continual Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Exploring Memorization in Adversarial Training.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks.
Proceedings of the Computer Vision - ECCV 2022, 2022

CoSCL: Cooperation of Small Continual Learners is Stronger Than a Big One.
Proceedings of the Computer Vision - ECCV 2022, 2022

BadDet: Backdoor Attacks on Object Detection.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

AutoLoss-GMS: Searching Generalized Margin-based Softmax Loss Function for Person Re-identification.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Analyzing the Noise Robustness of Deep Neural Networks.
IEEE Trans. Vis. Comput. Graph., 2021

Semiparametric method and theory for continuously indexed spatio-temporal processes.
J. Multivar. Anal., 2021

AdvCapsNet: To defense adversarial attacks based on Capsule networks.
J. Vis. Commun. Image Represent., 2021

Learning auto-scale representations for person re-identification.
Image Vis. Comput., 2021

Auto-ReID+: Searching for a multi-branch ConvNet for person re-identification.
Neurocomputing, 2021

Unrestricted Adversarial Attacks on ImageNet Competition.
CoRR, 2021

Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness.
CoRR, 2021

Adversarial Attacks on ML Defense Models Competition.
CoRR, 2021

TiKick: Towards Playing Multi-agent Football Full Games from Single-agent Demonstrations.
CoRR, 2021

Ranking Cost: Building An Efficient and Scalable Circuit Routing Planner with Evolution-Based Optimization.
CoRR, 2021

Adversarial Semantic Contour for Object Detection.
CoRR, 2021

Query-based Adversarial Attacks on Graph with Fake Nodes.
CoRR, 2021

Tianshou: a Highly Modularized Deep Reinforcement Learning Library.
CoRR, 2021

Query2Label: A Simple Transformer Way to Multi-Label Classification.
CoRR, 2021

Understanding Adversarial Attacks on Observations in Deep Reinforcement Learning.
CoRR, 2021

Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit.
CoRR, 2021

Pre-Trained Models: Past, Present and Future.
CoRR, 2021

KO-PDE: Kernel Optimized Discovery of Partial Differential Equations with Varying Coefficients.
CoRR, 2021

Adversarial Training with Rectified Rejection.
CoRR, 2021

Automated Decision-based Adversarial Attacks.
CoRR, 2021

Few-shot Continual Learning: a Brain-inspired Approach.
CoRR, 2021

Accurate and Reliable Forecasting using Stochastic Differential Equations.
CoRR, 2021

DNN2LR: Automatic Feature Crossing for Credit Scoring.
CoRR, 2021

Rethinking Natural Adversarial Examples for Classification Models.
CoRR, 2021

Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation.
CoRR, 2021

Pre-trained models: Past, present and future.
AI Open, 2021

Off-Policy Training for Truncated TD(λ) Boosted Soft Actor-Critic.
Proceedings of the PRICAI 2021: Trends in Artificial Intelligence, 2021

Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scalable Quasi-Bayesian Inference for Instrumental Variable Regression.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

AFEC: Active Forgetting of Negative Transfer in Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Accumulative Poisoning Attacks on Real-time Data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Stability and Generalization of Bilevel Programming in Hyperparameter Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models.
Proceedings of the 38th International Conference on Machine Learning, 2021

MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering.
Proceedings of the 9th International Conference on Learning Representations, 2021

Bag of Tricks for Adversarial Training.
Proceedings of the 9th International Conference on Learning Representations, 2021

Implicit Normalizing Flows.
Proceedings of the 9th International Conference on Learning Representations, 2021

Towards Face Encryption by Generating Adversarial Identity Masks.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Black-box Detection of Backdoor Attacks with Limited Information and Data.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Improving Transferability of Adversarial Patches on Face Recognition With Generative Models.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-Supervised Continual Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Unsupervised Part Segmentation Through Disentangling Appearance and Shape.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

LiBRe: A Practical Bayesian Approach to Adversarial Detection.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Mining Cross Features for Financial Credit Risk Assessment.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Learning Task-Distribution Reward Shaping with Meta-Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Improving Generative Moment Matching Networks with Distribution Partition.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs.
IEEE Trans. Parallel Distributed Syst., 2020

A Hierarchical Recurrent Neural Network for Symbolic Melody Generation.
IEEE Trans. Cybern., 2020

Towards a new generation of artificial intelligence in China.
Nat. Mach. Intell., 2020

Toward Accurate Visual Reasoning With Dual-Path Neural Module Networks.
Frontiers Robotics AI, 2020

Series Saliency: Temporal Interpretation for Multivariate Time Series Forecasting.
CoRR, 2020

Bi-level Score Matching for Learning Energy-based Latent Variable Models.
CoRR, 2020

BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayeisan Fine-tuning.
CoRR, 2020

Deep Active Learning by Model Interpretability.
CoRR, 2020

Delving into the Adversarial Robustness on Face Recognition.
CoRR, 2020

Efficient Learning of Generative Models via Finite-Difference Score Matching.
CoRR, 2020

Calibrated Reliable Regression using Maximum Mean Discrepancy.
CoRR, 2020

Dynamic Window-level Granger Causality of Multi-channel Time Series.
CoRR, 2020

Brain-inspired global-local hybrid learning towards human-like intelligence.
CoRR, 2020

Towards Privacy Protection by Generating Adversarial Identity Masks.
CoRR, 2020

Boosting Adversarial Training with Hypersphere Embedding.
CoRR, 2020

PopMNet: Generating structured pop music melodies using neural networks.
Artif. Intell., 2020

Exploration Analysis in Finite-Horizon Turn-based Stochastic Games.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Learning Implicit Generative Models by Teaching Density Estimators.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Multi-label classification: do Hamming loss and subset accuracy really conflict with each other?
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Boosting Adversarial Training with Hypersphere Embedding.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Learning of Generative Models via Finite-Difference Score Matching.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adversarial Distributional Training for Robust Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Understanding and Exploring the Network with Stochastic Architectures.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Calibrated Reliable Regression using Maximum Mean Discrepancy.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Bi-level Score Matching for Learning Energy-based Latent Variable Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Further Analysis of Outlier Detection with Deep Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Discrete Memory Addressing Variational Autoencoder for Visual Concept Learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Variance Reduction and Quasi-Newton for Particle-Based Variational Inference.
Proceedings of the 37th International Conference on Machine Learning, 2020

Nonparametric Score Estimators.
Proceedings of the 37th International Conference on Machine Learning, 2020

Understanding and Stabilizing GANs' Training Dynamics Using Control Theory.
Proceedings of the 37th International Conference on Machine Learning, 2020

VFlow: More Expressive Generative Flows with Variational Data Augmentation.
Proceedings of the 37th International Conference on Machine Learning, 2020

Lazy-CFR: fast and near-optimal regret minimization for extensive games with imperfect information.
Proceedings of the 8th International Conference on Learning Representations, 2020

Posterior sampling for multi-agent reinforcement learning: solving extensive games with imperfect information.
Proceedings of the 8th International Conference on Learning Representations, 2020

Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness.
Proceedings of the 8th International Conference on Learning Representations, 2020

SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models.
Proceedings of the 8th International Conference on Learning Representations, 2020

To Relieve Your Headache of Training an MRF, Take AdVIL.
Proceedings of the 8th International Conference on Learning Representations, 2020

SVQN: Sequential Variational Soft Q-Learning Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Design and Interpretation of Universal Adversarial Patches in Face Detection.
Proceedings of the Computer Vision - ECCV 2020, 2020

Training Interpretable Convolutional Neural Networks by Differentiating Class-Specific Filters.
Proceedings of the Computer Vision - ECCV 2020, 2020

Defense Against Adversarial Attacks via Controlling Gradient Leaking on Embedded Manifolds.
Proceedings of the Computer Vision - ECCV 2020, 2020

Benchmarking Adversarial Robustness on Image Classification.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Max-Margin Majority Voting for Learning from Crowds.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Stochastic gradient Hamiltonian Monte Carlo with variance reduction for Bayesian inference.
Mach. Learn., 2019

Towards controllable image descriptions with semi-supervised VAE.
J. Vis. Commun. Image Represent., 2019

Stochastic Quantization for Learning Accurate Low-Bit Deep Neural Networks.
Int. J. Comput. Vis., 2019

Benchmarking Adversarial Robustness.
CoRR, 2019

Design and Interpretation of Universal Adversarial Patches in Face Detection.
CoRR, 2019

DBSN: Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structures.
CoRR, 2019

Understanding and Stabilizing GANs' Training Dynamics with Control Theory.
CoRR, 2019

DashNet: A Hybrid Artificial and Spiking Neural Network for High-speed Object Tracking.
CoRR, 2019

A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels.
CoRR, 2019

Multi-objects Generation with Amortized Structural Regularization.
CoRR, 2019

DS<sup>3</sup>L: Deep Self-Semi-Supervised Learning for Image Recognition.
CoRR, 2019

Boosting Generative Models by Leveraging Cascaded Meta-Models.
CoRR, 2019

Reward Shaping via Meta-Learning.
CoRR, 2019

Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples.
CoRR, 2019

Adversarial Variational Inference and Learning in Markov Random Fields.
CoRR, 2019

Explainable AI: A Brief Survey on History, Research Areas, Approaches and Challenges.
Proceedings of the Natural Language Processing and Chinese Computing, 2019

Multi-objects Generation with Amortized Structural Regularization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Improving Black-box Adversarial Attacks with a Transfer-based Prior.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Playing FPS Games With Environment-Aware Hierarchical Reinforcement Learning.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

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

Improving Adversarial Robustness via Promoting Ensemble Diversity.
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

Function Space Particle Optimization for Bayesian Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Cluster Alignment With a Teacher for Unsupervised Domain Adaptation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Efficient Decision-Based Black-Box Adversarial Attacks on Face Recognition.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Learn a Robust Policy in Adversarial Games via Playing with an Expert Opponent.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Direct Training for Spiking Neural Networks: Faster, Larger, Better.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Sparse Adversarial Perturbations for Videos.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Composite Binary Decomposition Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Combo-Action: Training Agent For FPS Game with Auxiliary Tasks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 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 Networks Learn. Syst., 2018

Scalable Training of Hierarchical Topic Models.
Proc. VLDB Endow., 2018

Neural Network Meets DCN: Traffic-driven Topology Adaptation with Deep Learning.
Proc. ACM Meas. Anal. Comput. Syst., 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

Lazy-CFR: a fast regret minimization algorithm for extensive games with imperfect information.
CoRR, 2018

Direct Training for Spiking Neural Networks: Faster, Larger, Better.
CoRR, 2018

Deep Structured Generative Models.
CoRR, 2018

Learning Implicit Generative Models by Teaching Explicit Ones.
CoRR, 2018

Accelerated First-order Methods on the Wasserstein Space for Bayesian Inference.
CoRR, 2018

Adversarial Attacks and Defences Competition.
CoRR, 2018

Sparse Adversarial Perturbations for Videos.
CoRR, 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

Stochastic Expectation Maximization with Variance Reduction.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Video-to-Video Translation with Global Temporal Consistency.
Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 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

Analyzing the Noise Robustness of Deep Neural Networks.
Proceedings of the 13th IEEE Conference on Visual Analytics Science and Technology, 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.
Vis. 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

Online Bayesian Passive-Aggressive Learning.
J. Mach. Learn. Res., 2017

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

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

Learning Random Fourier Features by Hybrid Constrained Optimization.
CoRR, 2017

Stochastic Training of Graph Convolutional Networks.
CoRR, 2017

Discovering Adversarial Examples with Momentum.
CoRR, 2017

ZhuSuan: A Library for Bayesian Deep Learning.
CoRR, 2017

Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization.
CoRR, 2017

Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networks.
CoRR, 2017

Implicit Variational Inference with Kernel Density Ratio Fitting.
CoRR, 2017

Robust Deep Learning via Reverse Cross-Entropy Training and Thresholding Test.
CoRR, 2017

Triple Generative Adversarial Nets.
CoRR, 2017

SAM: Semantic Attribute Modulated Language Modeling.
CoRR, 2017

Scalable Inference for Nested Chinese Restaurant Process Topic Models.
CoRR, 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

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. Medical Imaging, 2016

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

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

Max-Margin Nonparametric Latent Feature Models for Link Prediction.
CoRR, 2016

SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data.
CoRR, 2016

Generative Topic Embedding: a Continuous Representation of Documents (Extended Version with Proofs).
CoRR, 2016

Streaming Gibbs Sampling for LDA Model.
CoRR, 2016

Collaborative Filtering with User-Item Co-Autoregressive Models.
CoRR, 2016

A Communication-Efficient Parallel Method for Group-Lasso.
CoRR, 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

Building Memory with Concept Learning Capabilities from Large-scale Knowledge Base.
CoRR, 2015

Fast Parallel SVM using Data Augmentation.
CoRR, 2015

Bounded-Distortion Metric Learning.
CoRR, 2015

Stochastic Subgradient MCMC Methods.
CoRR, 2015

Learning Deep Generative Models with Doubly Stochastic MCMC.
CoRR, 2015

WarpLDA: a Simple and Efficient O(1) Algorithm for Latent Dirichlet Allocation.
CoRR, 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 Networks Learn. 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

Big Learning with Bayesian Methods.
CoRR, 2014

Contrastive Feature Induction for Efficient Structure Learning of Conditional Random Fields.
CoRR, 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

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. Multim., 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

Dynamics of an ecological model with impulsive control strategy and distributed time delay.
Math. Comput. Simul., 2012

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

Bayesian Inference with Posterior Regularization and Infinite Latent Support Vector Machines
CoRR, 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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