Ratner, Alexander J

8 publications

NeurIPS 2023 Characterizing the Impacts of Semi-Supervised Learning for Weak Supervision Jeffrey Li, Jieyu Zhang, Ludwig Schmidt, Alexander J Ratner

NeurIPS 2023 DataComp: In Search of the Next Generation of Multimodal Datasets Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei W Koh, Olga Saukh, Alexander J Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt

NeurIPS 2023 Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander J Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang

NeurIPS 2023 On the Trade-Off of Intra-/Inter-Class Diversity for Supervised Pre-Training Jieyu Zhang, Bohan Wang, Zhengyu Hu, Pang Wei W Koh, Alexander J Ratner

NeurIPS 2022 Understanding Programmatic Weak Supervision via Source-Aware Influence Function Jieyu Zhang, Haonan Wang, Cheng-Yu Hsieh, Alexander J Ratner

NeurIPS 2019 Slice-Based Learning: A Programming Model for Residual Learning in Critical Data Slices Vincent Chen, Sen Wu, Alexander J Ratner, Jen Weng, Christopher Ré

NeurIPS 2017 Learning to Compose Domain-Specific Transformations for Data Augmentation Alexander J Ratner, Henry Ehrenberg, Zeshan Hussain, Jared Dunnmon, Christopher Ré

NeurIPS 2016 Data Programming: Creating Large Training Sets, Quickly Alexander J Ratner, Christopher M De Sa, Sen Wu, Daniel Selsam, Christopher Ré