Mussmann, Stephen

13 publications

DMLR 2024 LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning Jifan Zhang, Yifang Chen, Gregory Canal, Arnav Mohanty Das, Gantavya Bhatt, Stephen Mussmann, Yinglun Zhu, Jeff Bilmes, Simon Shaolei Du, Kevin Jamieson, Robert D Nowak

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

NeurIPSW 2023 LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning Jifan Zhang, Yifang Chen, Gregory Canal, Arnav Mohanty Das, Gantavya Bhatt, Yinglun Zhu, Stephen Mussmann, Simon Shaolei Du, Jeff Bilmes, Kevin Jamieson, Robert D Nowak

AISTATS 2021 Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation Mayee Chen, Benjamin Cohen-Wang, Stephen Mussmann, Frederic Sala, Christopher Re

ICML 2020 Concept Bottleneck Models Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang

NeurIPSW 2020 On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks Stephen Mussmann, Robin Jia, Percy Liang

ICLR 2020 Selection via Proxy: Efficient Data Selection for Deep Learning Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia

AISTATS 2018 Generalized Binary Search for Split-Neighborly Problems Stephen Mussmann, Percy Liang

ICML 2018 On the Relationship Between Data Efficiency and Error for Uncertainty Sampling Stephen Mussmann, Percy Liang

NeurIPS 2018 Uncertainty Sampling Is Preconditioned Stochastic Gradient Descent on Zero-One Loss Stephen Mussmann, Percy Liang

UAI 2017 Fast Amortized Inference and Learning in Log-Linear Models with Randomly Perturbed Nearest Neighbor Search Stephen Mussmann, Daniel Levy, Stefano Ermon

ICML 2016 Learning and Inference via Maximum Inner Product Search Stephen Mussmann, Stefano Ermon

AAAI 2015 Incorporating Assortativity and Degree Dependence into Scalable Network Models Stephen Mussmann, John Moore, Joseph John Pfeiffer Iii, Jennifer Neville