| 2015-07-31 | A Deterministic Partition Function Approximation for Exponential Random Graph Models | Pu, Wen; Choi, Jaesik; Hwang, Yunseong; Amir, Eyal | CONFERENCE | 117 |
| 2015-12 | A Scalable and Flexible Repository for Big Sensor Data | Lee, Dongeun; Choi, Jaesik; Shin, Heonshik | ARTICLE | 984 |
| 2020-06-02 | A Single Multi-Task Deep Neural Network with Post-Processing for Object Detection with Reasoning and Robotic Grasp Detection | Park, Dongwon; Seo, Yonghyeok; Shin, Dongju; Choi, Jaesik; Chun, Se Young | CONFERENCE | 68 |
| 2013-06 | A spatio-temporal pyramid matching for video retrieval | Choi, Jaesik; Wang, Ziyu; Lee, Sang-Chul; Jeon, Won J. | ARTICLE | 999 |
| 2018-02 | An Expectation Maximization Method to Learn the Group Structure of Deep Neural Network | Choi, Jaesik; Yi, Subin | Master's thesis | 1327 |
| 2016-06-21 | Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series | Hwang, Yunseong; Tong, Anh; Choi, Jaesik | CONFERENCE | 128 |
| 2017-08 | AUTOMATIC DECOMPOSITION OF SELF-TRIGGERING KERNELS OF HAWKES PROCESSES | Choi, Jaesik; Lima, Rafael Goncalves de | Master's thesis | 1247 |
| 2019-08-14 | Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes | Han, Jiyeon; Lee, Kyowoon; Tong, Anh; Choi, Jaesik | CONFERENCE | 133 |
| 2018-08 | DEEP FULLY RESIDUAL CONVOLUTIONAL NEURAL NETWORK FOR SEMANTIC IMAGE SEGMENTATION | Choi, Jaesik; Tousi, Ali | Master's thesis | 384 |
| 2019-08 | Deep Neural Networks to Learn Basis Functions with a Temporal Covariance Loss | Choi, Jaesik; Ju, Janghoon | Master's thesis | 440 |
| 2018-07-11 | Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling | Lee, Kyowoon; Kim, Sol-A; Choi, Jaesik; Lee, Seong-Whan | CONFERENCE | 130 |
| 2019-06-12 | Discovering Latent Covariance Structures for Multiple Time Series | Tong, Anh; Choi, Jaesik | CONFERENCE | 100 |
| 2018-12-13 | Dynamic Online Performance Optimization in Streaming Data Compression | Gibson, J. Kade; Lee, Dongeun; Choi, Jaesik; Sim, Alexander | CONFERENCE | 103 |
| 2017-04-04 | Expanding Statistical Similarity Based Data Reduction to Capture Diverse Patterns | Lee, Dongeun; Sim, Alex; Choi, Jaesik; Wu, Kesheng | CONFERENCE | 98 |
| 2015-12-20 | Extracting Baseline Electricity Usage Using Gradient Tree Boosting | Kim, Taehoon; Lee, Dongeun; Choi, Jaesik; Spurlock, Anna; Sim, Alex; Todd, Annika; Wu, Kesheng | CONFERENCE | 110 |
| 2013-10-06 | Fast Change Point Detection for Electricity Market Analysis | Gu, William; Choi, Jaesik; Gu, Ming; Simon, Horst; Wu, Kesheng | CONFERENCE | 97 |
| 2018-03 | Generative Design of Electromagnetic Structures Through Bayesian Learning | Patel, Ramesh; Roy, Kallol; Choi, Jaesik; Han, Ki Jin | ARTICLE | 672 |
| 2016-09-21 | Global Deconvolutional Networks for Semantic Segmentation | Nekrasov, Vladimir; Ju, Janghoon; Choi, Jaesik | CONFERENCE | 103 |
| 2020-07-16 | HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism | Park, Jay H.; Yun, Gyeongchan; Yi, Chang M.; Nguyen, Nguyen T.; Lee, Seungmin; Choi, Jaesik; Noh, Sam H.; Choi, Young-Ri | CONFERENCE | 179 |
| 2016-06-27 | Improving Imprecise Compressive Sensing Models | Lee, Dongeun; Lima, Rafael; Choi, Jaesik | CONFERENCE | 152 |
