Matt Jordan

According to our database, Matt Jordan authored at least 10 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

DataComp-LM: In search of the next generation of training sets for language models.

Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar

CoRR, 2024

MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens.

Anas Awadalla, Le Xue, Oscar Lo, Manli Shu, Hannah Lee, Etash Kumar Guha, Matt Jordan, Sheng Shen, Mohamed Awadalla, Silvio Savarese, Caiming Xiong, Ran Xu, Yejin Choi, Ludwig Schmidt

CoRR, 2024

Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand.

Md. Musfiqur Rahman, Matt Jordan, Murat Kocaoglu

CoRR, 2024

2022

Zonotope Domains for Lagrangian Neural Network Verification.

Matt Jordan, Jonathan Hayase, Alex Dimakis, Sewoong Oh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Inverse Problems Leveraging Pre-trained Contrastive Representations.

Sriram Ravula, Georgios Smyrnis, Matt Jordan, Alexandros G. Dimakis

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Provable Lipschitz Certification for Generative Models.

Matt Jordan, Alex Dimakis

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Quarantines as a Targeted Immunization Strategy.

Jessica Hoffmann, Matt Jordan, Constantine Caramanis

CoRR, 2020

Exactly Computing the Local Lipschitz Constant of ReLU Networks.

Matt Jordan, Alexandros G. Dimakis

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Quantifying Perceptual Distortion of Adversarial Examples.

Matt Jordan, Naren Manoj, Surbhi Goel, Alexandros G. Dimakis

CoRR, 2019

Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes.

Matt Jordan, Justin Lewis, Alexandros G. Dimakis

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019