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2020 – today
- 2023
[c11]Tianyi Liu, Zihao Xu, Hao He, Guang-Yuan Hao, Guang-He Lee, Hao Wang:
Taxonomy-Structured Domain Adaptation. ICML 2023: 22215-22232- [i9]Tianyi Liu, Zihao Xu, Hao He, Guang-Yuan Hao, Guang-He Lee, Hao Wang:
Taxonomy-Structured Domain Adaptation. CoRR abs/2306.07874 (2023) - 2022
- [c10]Zihao Xu, Hao He, Guang-He Lee, Bernie Wang, Hao Wang:
Graph-Relational Domain Adaptation. ICLR 2022 - [i8]Zihao Xu, Hao He, Guang-He Lee, Yuyang Wang, Hao Wang:
Graph-Relational Domain Adaptation. CoRR abs/2202.03628 (2022) - 2021
- [b1]Guang-He Lee:
Building Transparent Models. Massachusetts Institute of Technology, USA, 2021 - 2020
- [c9]Chen-Yu Hsu, Abbas Zeitoun, Guang-He Lee, Dina Katabi, Tommi S. Jaakkola:
Self-Supervised Learning of Appliance Usage. ICLR 2020 - [c8]Guang-He Lee, Tommi S. Jaakkola:
Oblique Decision Trees from Derivatives of ReLU Networks. ICLR 2020
2010 – 2019
- 2019
- [c7]Chen-Yu Hsu, Rumen Hristov, Guang-He Lee, Mingmin Zhao, Dina Katabi:
Enabling Identification and Behavioral Sensing in Homes using Radio Reflections. CHI 2019: 548 - [c6]Hao He, Hao Wang, Guang-He Lee, Yonglong Tian:
ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees. ICLR (Poster) 2019 - [c5]Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola:
Towards Robust, Locally Linear Deep Networks. ICLR (Poster) 2019 - [c4]Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola:
Functional Transparency for Structured Data: a Game-Theoretic Approach. ICML 2019: 3723-3733 - [c3]Guang-He Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola:
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers. NeurIPS 2019: 4911-4922 - [i7]Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola:
Functional Transparency for Structured Data: a Game-Theoretic Approach. CoRR abs/1902.09737 (2019) - [i6]Guang-He Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola:
A Stratified Approach to Robustness for Randomly Smoothed Classifiers. CoRR abs/1906.04948 (2019) - [i5]Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola:
Towards Robust, Locally Linear Deep Networks. CoRR abs/1907.03207 (2019) - [i4]Guang-He Lee, Tommi S. Jaakkola:
Locally Constant Networks. CoRR abs/1909.13488 (2019) - 2018
- [j1]Yonglong Tian, Guang-He Lee, Hao He, Chen-Yu Hsu, Dina Katabi:
RF-Based Fall Monitoring Using Convolutional Neural Networks. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2(3): 137:1-137:24 (2018) - [i3]Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola:
Game-Theoretic Interpretability for Temporal Modeling. CoRR abs/1807.00130 (2018) - 2017
- [c2]Guang-He Lee, Yun-Nung Chen:
MUSE: Modularizing Unsupervised Sense Embeddings. EMNLP 2017: 327-337 - [i2]Guang-He Lee, Yun-Nung Chen:
MUSE: Modularizing Unsupervised Sense Embeddings. CoRR abs/1704.04601 (2017) - 2016
- [i1]Guang-He Lee, Shao-Wen Yang, Shou-De Lin:
Toward Implicit Sample Noise Modeling: Deviation-driven Matrix Factorization. CoRR abs/1610.09274 (2016) - 2015
- [c1]Guang-He Lee, Shou-De Lin
:
LambdaMF: Learning Nonsmooth Ranking Functions in Matrix Factorization Using Lambda. ICDM 2015: 823-828
Coauthor Index
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