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20132022
most citedME-Net: Towards Effective Adversarial Robustness with Matrix Estimation

59 citations · 93 across the 7 of their papers we have counts for

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Showing cs.LGShow all

6 papers · 1 filter

cs.LG20221 cited

Contactless Oxygen Monitoring with Gated Transformer

Hao He, Yuan Yuan, Ying-Cong Chen +2

With the increasing popularity of telehealth, it becomes critical to ensure that basic physiological signals can be monitored accurately at home, with minimal patient overhead. In…

cs.LG2021

Delving into Deep Imbalanced Regression

Yuzhe Yang, Kaiwen Zha, Ying-Cong Chen +2

Real-world data often exhibit imbalanced distributions, where certain target values have significantly fewer observations. Existing techniques for dealing with imbalanced data focu…

cs.LG20208 cited

Continuously Indexed Domain Adaptation

Hao Wang, Hao He, Dina Katabi

Existing domain adaptation focuses on transferring knowledge between domains with categorical indices (e.g., between datasets A and B). However, many tasks involve continuously ind…

cs.LG2019

Learning Compositional Koopman Operators for Model-Based Control

Yunzhu Li, Hao He, Jiajun Wu +2

Finding an embedding space for a linear approximation of a nonlinear dynamical system enables efficient system identification and control synthesis. The Koopman operator theory lay…

cs.LG2019

Harnessing Structures for Value-Based Planning and Reinforcement Learning

Yuzhe Yang, Guo Zhang, Zhi Xu +1

Value-based methods constitute a fundamental methodology in planning and deep reinforcement learning (RL). In this paper, we propose to exploit the underlying structures of the sta…

cs.LG201959 cited

ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation

Yuzhe Yang, Guo Zhang, Dina Katabi +1

Deep neural networks are vulnerable to adversarial attacks. The literature is rich with algorithms that can easily craft successful adversarial examples. In contrast, the performan…