| RF-based fall monitoring using convolutional neural networks GH Lee*, Y Tian*, H He*, CY Hsu, D Katabi Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018 | 177 | 2018 |
| Tight certificates of adversarial robustness for randomly smoothed classifiers GH Lee, Y Yuan, S Chang, TS Jaakkola Neural Information Processing Systems (NeurIPS 2019), 2019 | 129 | 2019 |
| Enabling identification and behavioral sensing in homes using radio reflections CY Hsu, R Hristov, GH Lee, M Zhao, D Katabi Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems …, 2019 | 99 | 2019 |
| Dynamic sampling of sensor data GH Lee, SW Yang US Patent App. 16/062,107, 2018 | 92 | 2018 |
| Towards Robust, Locally Linear Deep Networks GH Lee, D Alvarez-Melis, TS Jaakkola International Conference on Learning Representations (ICLR 2019), 2019 | 46 | 2019 |
| MUSE: Modularizing Unsupervised Sense Embeddings GH Lee, YN Chen Empirical Methods in Natural Language Processing (EMNLP 2017), 327-337, 2017 | 44 | 2017 |
| ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees H He, H Wang, GH Lee, Y Tian International Conference on Learning Representations (ICLR 2019), 2019 | 42 | 2019 |
| Cost-sensitive classification with deep learning using cost-aware pre-training YA Chung, GH Lee, SW Yang US Patent 10,614,361, 2020 | 33 | 2020 |
| Adversarial Robustness Certificates: a Randomized Smoothing Approach J Teng, GH Lee, Y Yuan | 33 | 2020 |
| Graph-Relational Domain Adaptation Z Xu, GH Lee, Y Wang, H Wang International Conference on Learning Representations (ICLR 2022), 2022 | 27 | 2022 |
| Oblique Decision Trees from Derivatives of ReLU Networks GH Lee, TS Jaakkola International Conference on Learning Representations (ICLR 2020), 2020 | 26 | 2020 |
| Functional Transparency for Structured Data: a Game-Theoretic Approach GH Lee, W Jin, D Alvarez-Melis, TS Jaakkola International Conference on Machine Learning (ICML 2019), 2019 | 23 | 2019 |
| Canonicalizing bigsmiles for polymers with defined backbones TS Lin, NJ Rebello, GH Lee, MA Morris, BD Olsen ACS polymers Au 2 (6), 486-500, 2022 | 19 | 2022 |
| Self-Supervised Learning of Appliance Usage CY Hsu, A Zeitoun, GH Lee, D Katabi, T Jaakkola International Conference on Learning Representations (ICLR 2020), 2020 | 13 | 2020 |
| LambdaMF: Learning Nonsmooth Ranking Functions in Matrix Factorization Using Lambda GH Lee, SD Lin International Conference on Data Mining (ICDM 2015), 823-828, 2015 | 11 | 2015 |
| Bayesian Modelling and Monte Carlo Inference for GAN H He, H Wang, GH Lee, Y Tian The ICML 2018 workshop on Theoretical Foundations and Applications of Deep …, 2018 | 10 | 2018 |
| Game-Theoretic Interpretability for Temporal Modeling GH Lee, D Alvarez-Melis, TS Jaakkola The 5th Workshop on Fairness, Accountability, and Transparency in Machine …, 2018 | 8 | 2018 |
| Taxonomy-Structured Domain Adaptation T Liu, Z Xu, H He, GY Hao, GH Lee, H Wang International Conference on Machine Learning (ICML 2023), 2023 | 6 | 2023 |
| Toward implicit sample noise modeling: Deviation-driven matrix factorization GH Lee, SW Yang, SD Lin arXiv preprint arXiv:1610.09274, 2016 | 3 | 2016 |
| Subject identification in behavioral sensing systems D Katabi, RH Hristov, CY Hsu, GH Lee, M Zhao US Patent App. 16/860,591, 2020 | 2 | 2020 |
Tommi JaakkolaMITVerified email at csail.mit.edu
