Mao Ye

According to our database, Mao Ye authored at least 26 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Fine-Grained Gradient Restriction: A Simple Approach for Mitigating Catastrophic Forgetting.

Bo Liu, Mao Ye, Peter Stone, Qiang Liu

CoRR, 2024

VLMine: Long-Tail Data Mining with Vision Language Models.

Mao Ye, Gregory P. Meyer, Zaiwei Zhang, Dennis Park, Siva Karthik Mustikovela, Yuning Chai, Eric M. Wolff

CoRR, 2024

2023

Learning Diffusion Bridges on Constrained Domains.

Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Efficient Transformer-based 3D Object Detection with Dynamic Token Halting.

Mao Ye, Gregory P. Meyer, Yuning Chai, Qiang Liu

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

2022

First Hitting Diffusion Models.

Mao Ye, Lemeng Wu, Qiang Liu

CoRR, 2022

Let us Build Bridges: Understanding and Extending Diffusion Generative Models.

Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu

CoRR, 2022

Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems.

Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set.

Mao Ye, Qiang Liu

Proceedings of the Uncertainty in Artificial Intelligence, 2022

First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data.

Mao Ye, Lemeng Wu, Qiang Liu

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

Diffusion-based Molecule Generation with Informative Prior Bridges.

Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu

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

BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach.

Bo Liu, Mao Ye, Stephen Wright, Peter Stone, Qiang Liu

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

Centroid Approximation for Bootstrap: Improving Particle Quality at Inference.

Mao Ye, Qiang Liu

Proceedings of the International Conference on Machine Learning, 2022

2021

Centroid Approximation for Bootstrap.

Mao Ye, Qiang Liu

CoRR, 2021

argmax centroid.

Chengyue Gong, Mao Ye, Qiang Liu

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

VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments.

Lizhen Nie, Mao Ye, Qiang Liu, Dan Nicolae

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

MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training.

Chengyue Gong, Tongzheng Ren, Mao Ye, Qiang Liu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision.

Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data.

Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, Zeliang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal

CoRR, 2020

Steepest Descent Neural Architecture Optimization: Escaping Local Optimum with Signed Neural Splitting.

Lemeng Wu, Mao Ye, Qi Lei, Jason D. Lee, Qiang Liu

CoRR, 2020

MaxUp: A Simple Way to Improve Generalization of Neural Network Training.

ChengYue Gong, Tongzheng Ren, Mao Ye, Qiang Liu

CoRR, 2020

Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework.

Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu

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

Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough.

Mao Ye, Lemeng Wu, Qiang Liu

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

Stein Self-Repulsive Dynamics: Benefits From Past Samples.

Mao Ye, Tongzheng Ren, Qiang Liu

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

Go Wide, Then Narrow: Efficient Training of Deep Thin Networks.

Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans

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

Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection.

Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam R. Klivans, Qiang Liu

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

SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions.

Mao Ye, Chengyue Gong, Qiang Liu

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020