Chun-Nam Yu

According to our database, Chun-Nam Yu authored at least 12 papers between 2011 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

A Study on Representation Transfer for Few-Shot Learning.

Chun-Nam Yu, Yi Xie

CoRR, 2022

2019

DyMo: Dynamic Monitoring of Large-Scale LTE-Multicast Systems.

Yigal Bejerano, Chandrashekhar Raman, Chun-Nam Yu, Varun Gupta, Craig Gutterman, Tomas Young, Hugo Infante, Yousef Abdelmalek, Gil Zussman

IEEE/ACM Trans. Netw., 2019

A Direct Approach to Robust Deep Learning Using Adversarial Networks.

Huaxia Wang, Chun-Nam Yu

Proceedings of the 7th International Conference on Learning Representations, 2019

2017

A Sparse Coding Approach to Household Electricity Demand Forecasting in Smart Grids.

Chun-Nam Yu, Piotr Mirowski, Tin Kam Ho

IEEE Trans. Smart Grid, 2017

DyMo: Dynamic monitoring of large scale LTE-Multicast systems.

Yigal Bejerano, Chandru Raman, Chun-Nam Yu, Varun Gupta, Craig Gutterman, Tomas Young, Hugo Infante, Yousef Abdelmalek, Gil Zussman

Proceedings of the 2017 IEEE Conference on Computer Communications, 2017

Convolutional Neural Networks for Figure Extraction in Historical Technical Documents.

Chun-Nam Yu, Caleb Carson Levy, Iraj Saniee

Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition, 2017

2016

Online Algorithm for Approximate Quantile Queries on Sliding Windows.

Chun-Nam Yu, Michael S. Crouch, Ruichuan Chen, Alessandra Sala

Proceedings of the Experimental Algorithms - 15th International Symposium, 2016

2014

Demand Forecasting in Smart Grids.

Piotr Mirowski, Sining Chen, Tin Kam Ho, Chun-Nam Yu

Bell Labs Tech. J., 2014

Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification.

Junfeng Wen, Chun-Nam Yu, Russell Greiner

Proceedings of the 31th International Conference on Machine Learning, 2014

2012

Transductive Learning of Structural SVMs via Prior Knowledge Constraints.

Chun-Nam Yu

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

A Generalized Loop Correction Method for Approximate Inference in Graphical Models.

Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors.

Chun-Nam Yu, Russell Greiner, Hsiu-Chin Lin, Vickie Baracos

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011