Jordan, Michael I.

Smoothness Maximization Along a Predefined Path Accurately Predicts the Speed Profiles of Complex Arm Movements

Todorov, E., & Jordan, M. I. (1998) · Journal of Neurophysiology

Motor Control and AdaptationHuman Motion and Animation

Cited by 241

A Berkeley View of Systems Challenges for AI

Stoica, I., Song, D., Popa, R. A., Patterson, D., Mahoney, M. W., Katz, R., Joseph, A. D., Jordan, M., Hellerstein, J. M., Gonzalez, J. E., et al. (2017) · arXiv

Artificial Intelligence ApplicationsAdvanced Neural Network Applications

Cited by 171

Distribution-free, Risk-controlling Prediction Sets

Bates, S., Angelopoulos, A., Lei, L., Malik, J., & Jordan, M. (2021) · Journal of the ACM

Adversarial Robustness in Machine LearningMachine Learning and Algorithms

Cited by 144

Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference

Chiang, W.-L., Zheng, L., Sheng, Y., Angelopoulos, A. N., Li, T., Li, D., Zhang, H., Zhu, B., Jordan, M., Gonzalez, J. E., et al. (2024) · arXiv

Constraint Satisfaction and OptimizationNatural Language Processing Techniques

Cited by 118

A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements

Lopez, R., Nazaret, A., Langevin, M., Samaran, J., Regier, J., Jordan, M. I., & Yosef, N. (2019) · arXiv

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 105

Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control

Angelopoulos, A. N., Bates, S., Candès, E. J., Jordan, M. I., & Lei, L. (2021) · arXiv

Machine Learning and AlgorithmsMachine Learning and Data Classification

Cited by 100

Uncertainty Sets for Image Classifiers using Conformal Prediction

Angelopoulos, A., Bates, S., Malik, J., & Jordan, M. I. (2020) · arXiv

Adversarial Robustness in Machine LearningAdvanced Neural Network Applications

Cited by 79

Deep generative modeling of sample-level heterogeneity in single-cell genomics

Boyeau, P., Hong, J., Gayoso, A., Kim, M., McFaline-Figueroa, J. L., Jordan, M. I., Azizi, E., Ergen, C., & Yosef, N. (2025) · Nature Methods

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 55

Real-Time Machine Learning: The Missing Pieces

Nishihara, R., Moritz, P., Wang, S., Tumanov, A., Paul, W., Schleier-Smith, J., Liaw, R., Niknami, M., Jordan, M. I., & Stoica, I. (2017) · Proceedings of the 16th Workshop on Hot Topics in Operating Systems

Parallel Computing and Optimization TechniquesCloud Computing and Resource Management

Cited by 49

On kernel methods for covariates that are rankings

Mania, H., Ramdas, A., Wainwright, M. J., Jordan, M. I., & Recht, B. (2018) · Electronic Journal of Statistics

Machine Learning and ELMMachine Learning and Algorithms

Cited by 18

Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions

Lekeufack, J., Angelopoulos, A. N., Bajcsy, A., Jordan, M. I., & Malik, J. (2024) · 2024 IEEE International Conference on Robotics and Automation (ICRA)

Machine Learning and AlgorithmsAdversarial Robustness in Machine Learning

Cited by 18

ElegantRL-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement Learning

Liu, X.-Y., Li, Z., Yang, Z., Zheng, J., Wang, Z., Walid, A., Guo, J., & Jordan, M. I. (2021) · arXiv

Reinforcement Learning in RoboticsCloud Computing and Resource Management

Cited by 15

LS-Tree: Model Interpretation When the Data Are Linguistic

Chen, J., & Jordan, M. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Explainable Artificial Intelligence (XAI)Natural Language Processing Techniques

Cited by 14

Private Prediction Sets

Angelopoulos, A. N., Bates, S., Zrnic, T., & Jordan, M. I. (2022) · Harvard Data Science Review

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 8

Fine-Tuning Language Models with Advantage-Induced Policy Alignment

Zhu, B., Sharma, H., Frujeri, F. V., Dong, S., Zhu, C., Jordan, M. I., & Jiao, J. (2023) · arXiv

Reinforcement Learning in RoboticsTopic Modeling

Cited by 6

Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information

Rolf, E., Jordan, M. I., & Recht, B. (2020) · arXiv

Spatial and Panel Data AnalysisMachine Learning and Data Classification

Cited by 3

Towards Optimal Caching and Model Selection for Large Model Inference

Zhu, B., Sheng, Y., Zheng, L., Barrett, C., Jordan, M., & Jiao, J. (2023) · Advances in Neural Information Processing Systems 36

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 2

AutoEval Done Right: Using Synthetic Data for Model Evaluation

Boyeau, P., Angelopoulos, A. N., Yosef, N., Malik, J., & Jordan, M. I. (2024) · arXiv

Machine Learning and Data ClassificationMachine Learning and Algorithms

Cited by 1

Automatically Adaptive Conformal Risk Control

Blot, V., Angelopoulos, A. N., Jordan, M. I., & Brunel, N. J.-B. (2024) · arXiv

Machine Learning and AlgorithmsAdversarial Robustness in Machine Learning

Cited by 1