Yisen Wang

Zhouchen Lin

CoRR, 2024

A Theoretical Understanding of Self-Correction through In-context Alignment.

[BibT_eX]

[DOI]

CoRR, 2024

A Canonization Perspective on Invariant and Equivariant Learning.

[BibT_eX]

[DOI]

CoRR, 2024

How to Craft Backdoors with Unlabeled Data Alone?

[BibT_eX]

[DOI]

CoRR, 2024

FMM-Attack: A Flow-based Multi-modal Adversarial Attack on Video-based LLMs.

[BibT_eX]

[DOI]

CoRR, 2024

Studious Bob Fight Back Against Jailbreaking via Prompt Adversarial Tuning.

[BibT_eX]

[DOI]

CoRR, 2024

Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

PID: Prompt-Independent Data Protection Against Latent Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Non-negative Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Do Generated Data Always Help Contrastive Learning?

[BibT_eX]

[DOI]

Jizhe Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

On the Role of Discrete Tokenization in Visual Representation Learning.

[BibT_eX]

[DOI]

Tianqi Du

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

SPIDE: A purely spike-based method for training feedback spiking neural networks.

[BibT_eX]

[DOI]

Neural Networks, April, 2023

Equilibrium Image Denoising With Implicit Differentiation.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2023

Query efficient black-box adversarial attack on deep neural networks.

[BibT_eX]

[DOI]

Pattern Recognit., 2023

Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding.

[BibT_eX]

[DOI]

Jiangyan Ma

CoRR, 2023

Towards Control-Centric Representations in Reinforcement Learning from Images.

[BibT_eX]

[DOI]

CoRR, 2023

Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations.

[BibT_eX]

[DOI]

Zeming Wei

CoRR, 2023

Robust Long-Tailed Learning via Label-Aware Bounded CVaR.

[BibT_eX]

[DOI]

CoRR, 2023

Identifiable Contrastive Learning with Automatic Feature Importance Discovery.

[BibT_eX]

[DOI]

Qi Zhang

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

Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective.

[BibT_eX]

[DOI]

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

Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding.

[BibT_eX]

[DOI]

George Ma

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

Adversarial Examples Are Not Real Features.

[BibT_eX]

[DOI]

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

GEQ: Gaussian Kernel Inspired Equilibrium Models.

[BibT_eX]

[DOI]

Mingjie Li

Zhouchen Lin

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

Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning.

[BibT_eX]

[DOI]

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

On the Generalization of Multi-modal Contrastive Learning.

[BibT_eX]

[DOI]

Qi Zhang

Proceedings of the International Conference on Machine Learning, 2023

Rethinking Weak Supervision in Helping Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning.

[BibT_eX]

[DOI]

Rundong Luo

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Message Passing Perspective on Learning Dynamics of Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

CFA: Class-Wise Calibrated Fair Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Generalist: Decoupling Natural and Robust Generalization.

[BibT_eX]

[DOI]

Hongjun Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Training much deeper spiking neural networks with a small number of time-steps.

[BibT_eX]

[DOI]

Neural Networks, 2022

Proving Common Mechanisms Shared by Twelve Methods of Boosting Adversarial Transferability.

[BibT_eX]

[DOI]

CoRR, 2022

How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders.

[BibT_eX]

[DOI]

Qi Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

G<sup>2</sup>CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

CerDEQ: Certifiable Deep Equilibrium Model.

[BibT_eX]

[DOI]

Mingjie Li

Zhouchen Lin

Proceedings of the International Conference on Machine Learning, 2022

Certified Adversarial Robustness Under the Bounded Support Set.

[BibT_eX]

[DOI]

Yiwen Kou

Qinyuan Zheng

Proceedings of the International Conference on Machine Learning, 2022

Optimization-Induced Graph Implicit Nonlinear Diffusion.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Self-ensemble Adversarial Training for Improved Robustness.

[BibT_eX]

[DOI]

Hongjun Wang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Optimization inspired Multi-Branch Equilibrium Models.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Efficient and Scalable Implicit Graph Neural Networks with Virtual Equilibrium.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Understanding adversarial attacks on deep learning based medical image analysis systems.

[BibT_eX]

[DOI]

Pattern Recognit., 2021

Clustering Effect of (Linearized) Adversarial Robust Models.

[BibT_eX]

[DOI]

CoRR, 2021

Fooling Adversarial Training with Inducing Noise.

[BibT_eX]

[DOI]

Zhirui Wang

CoRR, 2021

Moiré Attack (MA): A New Potential Risk of Screen Photos.

[BibT_eX]

[DOI]

Dantong Niu

Ruohao Guo

CoRR, 2021

Optimization Induced Equilibrium Networks.

[BibT_eX]

[DOI]

CoRR, 2021

Game-theoretic Understanding of Adversarially Learned Features.

[BibT_eX]

[DOI]

CoRR, 2021

What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space.

[BibT_eX]

[DOI]

CoRR, 2021

Adversarial Interaction Attack: Fooling AI to Misinterpret Human Intentions.

[BibT_eX]

[DOI]

CoRR, 2021

Improving Generalization of Deep Reinforcement Learning-based TSP Solvers.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Reparameterized Sampling for Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarial Neuron Pruning Purifies Backdoored Deep Models.

[BibT_eX]

[DOI]

Dongxian Wu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Dissecting the Diffusion Process in Linear Graph Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Residual Relaxation for Multi-view Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Morié Attack (MA): A New Potential Risk of Screen Photos.

[BibT_eX]

[DOI]

Dantong Niu

Ruohao Guo

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Gauge Equivariant Transformer.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Efficient Equivariant Network.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Training Implicit Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Clustering Effect of Adversarial Robust Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Analysis and Applications of Class-wise Robustness in Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Leveraged Weighted Loss for Partial Label Learning.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

GBHT: Gradient Boosting Histogram Transform for Density Estimation.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

A Unified Approach to Interpreting and Boosting Adversarial Transferability.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Unlearnable Examples: Making Personal Data Unexploitable.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Improving Adversarial Robustness via Channel-wise Activation Suppressing.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Revisiting Loss Landscape for Adversarial Robustness.

[BibT_eX]

[DOI]

Dongxian Wu

Shutao Xia

CoRR, 2020

Adversarial Weight Perturbation Helps Robust Generalization.

[BibT_eX]

[DOI]

Dongxian Wu

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

Temporal Calibrated Regularization for Robust Noisy Label Learning.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Improving Gravitational Wave Detection with 2D Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Normalized Loss Functions for Deep Learning with Noisy Labels.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Improving Adversarial Robustness Requires Revisiting Misclassified Examples.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Improving Query Efficiency of Black-Box Adversarial Attack.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Adversarial Camouflage: Hiding Physical-World Attacks With Natural Styles.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Collaborative Representation Cascade for Single-Image Super-Resolution.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Syst., 2019

Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation.

[BibT_eX]

[DOI]

CoRR, 2019

On the Convergence and Robustness of Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Self-Attentive Networks for one-shot Image Recognition.

[BibT_eX]

[DOI]

Pin Fang

Yuan Luo

Proceedings of the IEEE International Conference on Multimedia and Expo, 2019

Hilbert-Based Generative Defense for Adversarial Examples.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Symmetric Cross Entropy for Robust Learning With Noisy Labels.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in Dialogue Generation.

[BibT_eX]

[DOI]

Min Zeng

Sudanthi N. R. Wijewickrema

Yuan Luo

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

A Novel Consistent Random Forest Framework: Bernoulli Random Forests.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2018

Learning Deep Hidden Nonlinear Dynamics from Aggregate Data.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Dimensionality-Driven Learning with Noisy Labels.

[BibT_eX]

[DOI]

James Bailey

Proceedings of the 35th International Conference on Machine Learning, 2018

Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality.

[BibT_eX]

[DOI]

Sudanthi N. R. Wijewickrema

Proceedings of the 6th International Conference on Learning Representations, 2018

Iterative Learning With Open-Set Noisy Labels.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Decoupled Networks.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

A less-greedy two-term Tsallis Entropy Information Metric approach for decision tree classification.

[BibT_eX]

[DOI]

Jia Wu

Knowl. Based Syst., 2017

A generic denoising framework via guided principal component analysis.

[BibT_eX]

[DOI]

J. Vis. Commun. Image Represent., 2017

Link sign prediction by Variational Bayesian Probabilistic Matrix Factorization with Student-t Prior.

[BibT_eX]

[DOI]

Inf. Sci., 2017

Residual Convolutional CTC Networks for Automatic Speech Recognition.

[BibT_eX]

[DOI]

CoRR, 2017

Student-t Process Regression with Student-t Likelihood.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Robust Survey Aggregation with Student-t Distribution and Sparse Representation.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Unifying attribute splitting criteria of decision trees by Tsallis entropy.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Unbiased Multivariate Correlation Analysis.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

End-to-end coding for TCP.

[BibT_eX]

[DOI]

IEEE Netw., 2016

A novel feature subspace selection method in random forests for high dimensional data.

[BibT_eX]

[DOI]

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Improving decision trees by Tsallis Entropy Information Metric method.

[BibT_eX]

[DOI]

Chao-Bing Song

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Bernoulli Random Forests: Closing the Gap between Theoretical Consistency and Empirical Soundness.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Student-t Process Regression with Dependent Student-t Noise.

[BibT_eX]

[DOI]

Qingtao Tang

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015

Improving Decision Trees Using Tsallis Entropy.

[BibT_eX]

[DOI]

Chao-Bing Song