Yifei Wang

Orcid: 0000-0002-0688-6012

Affiliations:
  • Peking University, School of Mathematical Sciences, China


According to our database1, Yifei Wang authored at least 34 papers between 2020 and 2024.

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Bibliography

2024
Non-negative Contrastive Learning.
CoRR, 2024

Do Generated Data Always Help Contrastive Learning?
CoRR, 2024

2023
Equilibrium Image Denoising With Implicit Differentiation.
IEEE Trans. Image Process., 2023

Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding.
CoRR, 2023

Towards Control-Centric Representations in Reinforcement Learning from Images.
CoRR, 2023

Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations.
CoRR, 2023

Robust Long-Tailed Learning via Label-Aware Bounded CVaR.
CoRR, 2023

Identifiable Contrastive Learning with Automatic Feature Importance Discovery.
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.
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.
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.
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.
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.
Proceedings of the International Conference on Machine Learning, 2023

Rethinking Weak Supervision in Helping Contrastive Learning.
Proceedings of the International Conference on Machine Learning, 2023

Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Message Passing Perspective on Learning Dynamics of Contrastive Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

CFA: Class-Wise Calibrated Fair Adversarial Training.
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.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders.
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.
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.
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.
Proceedings of the International Conference on Machine Learning, 2022

Optimization-Induced Graph Implicit Nonlinear Diffusion.
Proceedings of the International Conference on Machine Learning, 2022

Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap.
Proceedings of the Tenth International Conference on Learning Representations, 2022

A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Efficient and Scalable Implicit Graph Neural Networks with Virtual Equilibrium.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Fooling Adversarial Training with Inducing Noise.
CoRR, 2021

Reparameterized Sampling for Generative Adversarial Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Dissecting the Diffusion Process in Linear Graph Convolutional Networks.
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.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Decoder-free Robustness Disentanglement without (Additional) Supervision.
CoRR, 2020


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