Mucong Ding - RankMe

29 papers A* 8A 3Journal 18

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	PICore: Physics-Informed Unsupervised Coreset Selection for Data Efficient Neural Operator Training. CoRR Anirudh Satheesh, Anant Khandelwal, Mucong Ding, Radu Balan
2025	J	`jnl`	PICore: Physics-Informed Unsupervised Coreset Selection for Data Efficient Neural Operator Training. Trans. Mach. Learn. Res. Anirudh Satheesh, Anant Khandelwal, Mucong Ding, Radu Balan
2024	J	`jnl`	Benchmarking the Robustness of Image Watermarks. CoRR Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang
2024	J	`jnl`	Calibrated Dataset Condensation for Faster Hyperparameter Search. CoRR Mucong Ding, Yuancheng Xu, Tahseen Rabbani, Xiaoyu Liu, Brian J. Gravelle, Teresa M. Ranadive, Tai-Ching Tuan, Furong Huang
2024	A*	`conf`	Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization. NeurIPS Mucong Ding, Chenghao Deng, Jocelyn Choo, Zichu Wu, Aakriti Agrawal, Avi Schwarzschild, Tianyi Zhou, Tom Goldstein, John Langford, Animashree Anandkumar, Furong Huang
2024	J	`jnl`	Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization. CoRR Mucong Ding, Chenghao Deng, Jocelyn Choo, Zichu Wu, Aakriti Agrawal, Avi Schwarzschild, Tianyi Zhou, Tom Goldstein, John Langford, Anima Anandkumar, Furong Huang
2024	J	`jnl`	EnsemW2S: Can an Ensemble of LLMs be Leveraged to Obtain a Stronger LLM? CoRR Aakriti Agrawal, Mucong Ding, Zora Che, Chenghao Deng, Anirudh Satheesh, John Langford, Furong Huang
2024	A*	`conf`	SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation. ICLR Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang
2024	J	`jnl`	SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation. CoRR Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang
2024	J	`jnl`	SAIL: Self-Improving Efficient Online Alignment of Large Language Models. CoRR Mucong Ding, Souradip Chakraborty, Vibhu Agrawal, Zora Che, Alec Koppel, Mengdi Wang, Amrit S. Bedi, Furong Huang
2024	J	`jnl`	Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity. CoRR Mucong Ding, Tahseen Rabbani, Bang An, Evan Z. Wang, Furong Huang
2024	J	`jnl`	Spectral Greedy Coresets for Graph Neural Networks. CoRR Mucong Ding, Yinhan He, Jundong Li, Furong Huang
2024	A*	`conf`	WAVES: Benchmarking the Robustness of Image Watermarks. ICML Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang
2022	A*	`conf`	Robust Optimization as Data Augmentation for Large-scale Graphs. CVPR Kezhi Kong, Guohao Li, Mucong Ding, Zuxuan Wu, Chen Zhu, Bernard Ghanem, Gavin Taylor, Tom Goldstein
2022	A*	`conf`	Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity. NeurIPS Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang
2022	A*	`conf`	Transferring Fairness under Distribution Shifts via Fair Consistency Regularization. NeurIPS Bang An, Zora Che, Mucong Ding, Furong Huang
2022	J	`jnl`	Transferring Fairness under Distribution Shifts via Fair Consistency Regularization. CoRR Bang An, Zora Che, Mucong Ding, Furong Huang
2021	A	`conf`	GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences. AISTATS Mucong Ding, Constantinos Daskalakis, Soheil Feizi
2021	A*	`conf`	Understanding Over-parameterization in Generative Adversarial Networks. ICLR Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi
2021	J	`jnl`	Understanding Overparameterization in Generative Adversarial Networks. CoRR Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi
2021	A*	`conf`	VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization. NeurIPS Mucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John Dickerson, Furong Huang, Tom Goldstein
2021	J	`jnl`	VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization. CoRR Mucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John P. Dickerson, Furong Huang, Tom Goldstein
2020	J	`jnl`	FLAG: Adversarial Data Augmentation for Graph Neural Networks. CoRR Kezhi Kong, Guohao Li, Mucong Ding, Zuxuan Wu, Chen Zhu, Bernard Ghanem, Gavin Taylor, Tom Goldstein
2020	J	`jnl`	Subadditivity of Probability Divergences on Bayes-Nets with Applications to Time Series GANs. CoRR Mucong Ding, Constantinos Daskalakis, Soheil Feizi
2019	A	`conf`	Effective Feature Learning with Unsupervised Learning for Improving the Predictive Models in Massive Open Online Courses. LAK Mucong Ding, Kai Yang, Dit-Yan Yeung, Ting-Chuen Pong
2019	A	`conf`	Transfer Learning using Representation Learning in Massive Open Online Courses. LAK Mucong Ding, Yanbang Wang, Erik Hemberg, Una-May O'Reilly
2018	J	`jnl`	Effective Feature Learning with Unsupervised Learning for Improving the Predictive Models in Massive Open Online Courses. CoRR Mucong Ding, Kai Yang, Dit-Yan Yeung, Ting-Chuen Pong
2018	J	`jnl`	First-passage time distribution for random walks on complex networks using inverse Laplace transform and mean-field approximation. CoRR Mucong Ding, Kwok Yip Szeto
2018	J	`jnl`	Transfer Learning using Representation Learning in Massive Open Online Courses. CoRR Mucong Ding, Yanbang Wang, Erik Hemberg, Una-May O'Reilly