Mao Ye - RankMe

42 papers A* 17A 2Journal 22Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Generative Data Mining with Longtail-Guided Diffusion. ICML David S. Hayden, Mao Ye, Timur Garipov, Gregory P. Meyer, Carl Vondrick, Zhao Chen, Yuning Chai, Eric M. Wolff, Siddhartha S. Srinivasa
2025	J	`jnl`	Generative Data Mining with Longtail-Guided Diffusion. CoRR David S. Hayden, Mao Ye, Timur Garipov, Gregory P. Meyer, Carl Vondrick, Zhao Chen, Yuning Chai, Eric M. Wolff, Siddhartha S. Srinivasa
2025	—	`conf`	VLMine: Long-Tail Data Mining with Vision Language Models. WACV (Workshops) Mao Ye, Gregory P. Meyer, Zaiwei Zhang, Dennis Park, Siva Karthik Mustikovela, Yuning Chai, Eric M. Wolff
2024	J	`jnl`	Fine-Grained Gradient Restriction: A Simple Approach for Mitigating Catastrophic Forgetting. CoRR Bo Liu, Mao Ye, Peter Stone, Qiang Liu
2024	J	`jnl`	VLMine: Long-Tail Data Mining with Vision Language Models. CoRR Mao Ye, Gregory P. Meyer, Zaiwei Zhang, Dennis Park, Siva Karthik Mustikovela, Yuning Chai, Eric M. Wolff
2023	A*	`conf`	Efficient Transformer-based 3D Object Detection with Dynamic Token Halting. ICCV Mao Ye, Gregory P. Meyer, Yuning Chai, Qiang Liu
2023	J	`jnl`	Efficient Transformer-based 3D Object Detection with Dynamic Token Halting. CoRR Mao Ye, Gregory P. Meyer, Yuning Chai, Qiang Liu
2023	A*	`conf`	Learning Diffusion Bridges on Constrained Domains. ICLR Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu
2022	A*	`conf`	BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach. NeurIPS Bo Liu, Mao Ye, Stephen Wright, Peter Stone, Qiang Liu
2022	J	`jnl`	BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach. CoRR Mao Ye, Bo Liu, Stephen Wright, Peter Stone, Qiang Liu
2022	A*	`conf`	Centroid Approximation for Bootstrap: Improving Particle Quality at Inference. ICML Mao Ye, Qiang Liu
2022	A*	`conf`	Diffusion-based Molecule Generation with Informative Prior Bridges. NeurIPS Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu
2022	J	`jnl`	Diffusion-based Molecule Generation with Informative Prior Bridges. CoRR Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu
2022	A*	`conf`	First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data. NeurIPS Mao Ye, Lemeng Wu, Qiang Liu
2022	J	`jnl`	First Hitting Diffusion Models. CoRR Mao Ye, Lemeng Wu, Qiang Liu
2022	J	`jnl`	Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems. CoRR Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu
2022	A	`conf`	Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems. UAI Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu
2022	J	`jnl`	Let us Build Bridges: Understanding and Extending Diffusion Generative Models. CoRR Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu
2022	A	`conf`	Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set. UAI Mao Ye, Qiang Liu
2021	J	`jnl`	Centroid Approximation for Bootstrap. CoRR Mao Ye, Qiang Liu
2021	A*	`conf`	MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training. CVPR Chengyue Gong, Tongzheng Ren, Mao Ye, Qiang Liu
2021	J	`jnl`	Pareto Navigation Gradient Descent: a First-Order Algorithm for Optimization in Pareto Set. CoRR Mao Ye, Qiang Liu
2021	A*	`conf`	Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision. AAAI Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu
2021	A*	`conf`	VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments. ICLR Lizhen Nie, Mao Ye, Qiang Liu, Dan Nicolae
2021	J	`jnl`	VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments. CoRR Lizhen Nie, Mao Ye, Qiang Liu, Dan Nicolae
2021	A*	`conf`	argmax centroid. NeurIPS Chengyue Gong, Mao Ye, Qiang Liu
2020	J	`jnl`	Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data. CoRR Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, ZeLiang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal
2020	A*	`conf`	Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. NeurIPS Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu
2020	J	`jnl`	Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. CoRR Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu
2020	A*	`conf`	Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. ICML Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans
2020	J	`jnl`	Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. CoRR Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans
2020	A*	`conf`	Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection. ICML Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam R. Klivans, Qiang Liu
2020	J	`jnl`	Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection. CoRR Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam R. Klivans, Qiang Liu
2020	A*	`conf`	Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough. NeurIPS Mao Ye, Lemeng Wu, Qiang Liu
2020	J	`jnl`	Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough. CoRR Mao Ye, Lemeng Wu, Qiang Liu
2020	J	`jnl`	MaxUp: A Simple Way to Improve Generalization of Neural Network Training. CoRR Chengyue Gong, Tongzheng Ren, Mao Ye, Qiang Liu
2020	J	`jnl`	Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision. CoRR Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu
2020	A*	`conf`	SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions. ACL Mao Ye, Chengyue Gong, Qiang Liu
2020	J	`jnl`	SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions. CoRR Mao Ye, Chengyue Gong, Qiang Liu
2020	J	`jnl`	Steepest Descent Neural Architecture Optimization: Escaping Local Optimum with Signed Neural Splitting. CoRR Lemeng Wu, Mao Ye, Qi Lei, Jason D. Lee, Qiang Liu
2020	A*	`conf`	Stein Self-Repulsive Dynamics: Benefits From Past Samples. NeurIPS Mao Ye, Tongzheng Ren, Qiang Liu
2020	J	`jnl`	Stein Self-Repulsive Dynamics: Benefits From Past Samples. CoRR Mao Ye, Tongzheng Ren, Qiang Liu