Kangwook Lee
 |
Assistant Professor |
Email : first_name.last_name at wisc dot edu
Office : M1002G, Engineering Centers Building
Phone : +1-608-265-4841
Webpage : http://kangwooklee.com
Google Scholar : http://scholar.google.com/citations?user=sCEl8r-n5VEC&hl=en
News
(Oct. 2020) Our project on ‘GAN-mixup’ is chosen as a recipient of American Family Funding Initiative Awards!
(Sep. 2020) Our work on robust federated learning is accepted to NeurIPS 2020. ‘‘Attack of the Tails: Yes, You Really Can Backdoor Federated Learning’’.
(Aug. 2020) Liu joined the lab! Liu will be co-advised with Prof. Rob Nowak and Prof. Dimitris Papailiopoulos. Welcome!
(Aug. 2020) Nayoung joined the lab! Nayoung will be co-advised with Prof. Dimitris Papailiopoulos. Welcome!
(July 2020) Tuan Dinh joined the lab! Welcome!
(July 2020) Our project on distributed learning for the nomadic edge is chosen as a recipient of NSF/Intel Partnership on Machine Learning for Wireless Networking Systems (MLWiNS)!
(July 2020) Our new work on robust federated learning is available on Arxiv. ‘‘Attack of the Tails: Yes, You Really Can Backdoor Federated Learning’’.
(June 2020) Our new work on GAN-mixup is accepted to ICML 2020 Workshop on Uncertainty & Robustness in Deep Learning, ‘‘GAN-mixup: Augmenting Across Data Manifolds for Improved Robustness’’
(June 2020) Our work on ‘coded computation’ received the Joint Communications Society/Information Theory Society Paper Award!
K. Lee, M. Lam, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran, “Speeding up Distributed Machine Learning Using Codes”, IEEE Transactions on Information Theory, vol. 64, no. 3, pp. 1514-1529, March 2018(June 2020) Our project on interdisciplinary engineering of quantum information systems is chosen for the UW 2020: WARF Discovery Initiative!
(June 2020) Our new work on GAN reprogramming is accepted to ECML PKDD 2020. ‘‘Reprogramming GANs via Input Noise Design’’.
(May 2020) Our work on trustworthy AI is accepted to ICML 2020. ‘‘FR-Train: A mutual information-based approach to fair and robust training’’.
(May 2020) Gave a talk at Air Force Research Laboratory’s Virtual Workshop on Adversarial Robustness of Machine Learning, ‘‘FR-Train: A mutual information-based approach to fair and robust training’’
(Mar. 2020) Our new work on matrix completion with graph side information is available on Arxiv. ‘‘Discrete-valued Preference Estimation with Graph Side Information’’.
(Mar. 2020) Zhixu Du joined the lab! Welcome!
(Feb. 2020) Our new work on trustworthy AI is available on Arxiv, ‘‘FR-Train: A mutual information-based approach to fair and robust training’’.
(Feb. 2020) Gave an invited talk at the Chaos and Complex Systems Seminar @ UW-Madison.
(Jan. 2020) Dr. Daewon Seo joined the lab! Welcome!
(Jan. 2020) Gave invited talks at SK T-Brain and Furiosa.ai.
(Nov. 2019) Changhun Jo and Hyecheol Jang joined the lab! Welcome!
(Nov. 2019) Gave an invited talk at KOCSEA. ‘‘Information Theory and Coding for Machine Learning at Scale’’
(Oct. 2019) Jy-yong Sohn (co-hosted with Prof. Dimitris Papailiopoulos) will visit the lab for five months! Welcome!
(Oct. 2019) NeurIPS 2019 Workshop on Meta-Learning (MetaLearn 2019), ‘‘Improving Model Robustness via Automatically Incorporating Self-supervision Tasks’’
(Oct. 2019) Gave an invited talk at SILO seminar. ‘‘Learning with Scarce Data: The Role of Side Information, Simulators, and GANs’’
(Aug. 2019) Joined UW-Madison!