Interpreting CNNs via Decision Trees. - Quanshi Zhang; Yu Yang 007; Ying Nian Wu; Song-Chun Zhu (CoRR, 2018)

Network Transplanting. - Quanshi Zhang; Yu Yang 007; Ying Nian Wu; Song-Chun Zhu (CoRR, 2018)

Unsupervised Learning of Neural Networks to Explain Neural Networks. - Quanshi Zhang; Yu Yang 007; Yuchen Liu; Ying Nian Wu; Song-Chun Zhu (CoRR, 2018)

Interpreting CNNs via Decision Trees. - Quanshi Zhang; Yu Yang 007; Haotian Ma; Ying Nian Wu (CVPR, 2019)

Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks. - Zenan Ling; Haotian Ma; Yu Yang 007; Robert C. Qiu; Song-Chun Zhu; Quanshi Zhang (CoRR, 2019)

Network Transplanting (extended abstract). - Quanshi Zhang; Yu Yang 007; Qian Yu; Ying Nian Wu (CoRR, 2019)

Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract). - Quanshi Zhang; Yu Yang 007; Ying Nian Wu (CoRR, 2019)

A Generative Model for Sampling High-Performance and Diverse Weights for Neural Networks. - Lior Deutsch; Erik Nijkamp; Yu Yang 007 (CoRR, 2019)

Visual graph mining for graph matching. - Quanshi Zhang; Xuan Song 001; Yu Yang 007; Haotian Ma; Ryosuke Shibasaki (Comput. Vis. Image Underst., 2019)

Not All Poisons are Created Equal: Robust Training against Data Poisoning. - Yu Yang 007; Tian Yu Liu; Baharan Mirzasoleiman (ICML, 2022)

Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attack. - Tian Yu Liu; Yu Yang 007; Baharan Mirzasoleiman (NeurIPS, 2022)

Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks. - Tian Yu Liu; Yu Yang 007; Baharan Mirzasoleiman (CoRR, 2022)

NeSSA: Near-Storage Data Selection for Accelerated Machine Learning Training. - Neha Prakriya; Yu Yang 007; Baharan Mirzasoleiman; Cho-Jui Hsieh; Jason Cong (HotStorage, 2023)

Towards Sustainable Learning: Coresets for Data-efficient Deep Learning. - Yu Yang 007; Hao Kang; Baharan Mirzasoleiman (ICML, 2023)

Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning. - Yu Yang 007; Besmira Nushi; Hamid Palangi; Baharan Mirzasoleiman (ICML, 2023)

Robust Learning with Progressive Data Expansion Against Spurious Correlation. - Yihe Deng; Yu Yang 007; Baharan Mirzasoleiman; Quanquan Gu (NeurIPS, 2023)

Network Transplanting for the Functionally Modular Architecture. - Quanshi Zhang; Xu Cheng 005; Xin Wang 108; Yu Yang 007; Yingnian Wu (PRCV (3), 2023)

Eliminating Spurious Correlations from Pre-trained Models via Data Mixing. - Yihao Xue; Ali Payani; Yu Yang 007; Baharan Mirzasoleiman (CoRR, 2023)

Towards Mitigating Spurious Correlations in the Wild: A Benchmark & a more Realistic Dataset. - Siddharth Joshi 004; Yu Yang 007; Yihao Xue; Wenhan Yang; Baharan Mirzasoleiman (CoRR, 2023)

Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias. - Yu Yang 007; Eric Gan; Gintare Karolina Dziugaite; Baharan Mirzasoleiman (AISTATS, 2024)

Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality. - Xuxi Chen; Yu Yang 007; Zhangyang Wang; Baharan Mirzasoleiman (ICLR, 2024)

Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings. - Yihao Xue; Ali Payani; Yu Yang 007; Baharan Mirzasoleiman (ICML, 2024)

SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models. - Yu Yang 007; Siddhartha Mishra; Jeffrey N. Chiang; Baharan Mirzasoleiman (NeurIPS, 2024)

Memory-efficient Training of LLMs with Larger Mini-batches. - Dang Nguyen; Wenhan Yang; Rathul Anand; Yu Yang 007; Baharan Mirzasoleiman (CoRR, 2024)

Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures. - Dang Nguyen; Wenhan Yang; Rathul Anand; Yu Yang 007; Baharan Mirzasoleiman (ICLR, 2025)