Browse "School of Computing(전산학부)" by Type Conference
Showing results 3341 to 3360 of 7390
| Lazy Net: Lazy Entry Neural Networks for Accelerated and Efficient Inference Park, Junyong; Kim, Daeyoung; Moon, Yong-Hyuk, 13th International Conference on Information and Communication Technology Convergence, ICTC 2022, pp.495 - 497, IEEE Computer Society, 2022-10 |
| Learnersourcing Modular and Dynamic Multiple Choice Questions Kim, Haesoo; Song, Inhwa; Kim, Juho, 1st Annual Workshop on Learnersourcing: Student-Generated Content @ Scale, LSGCS 2022, pp.30 - 34, ACM, 2022-06-01 |
| Learnersourcing Subgoal Hierarchies of Code Examples Jin, Hyoungwook; Kim, Juho, 1st Annual Workshop on Learnersourcing: Student-Generated Content @ Scale, LSGCS 2022, pp.35 - 39, CEUR-WS, 2022-06-01 |
| Learnersourcing subgoal labels for how-To videos Weir, Sarah; Kim, Juho; Gajos, Krzysztof Z.; Miller, Robert C., 18th ACM International Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2015, pp.405 - 416, ACM Special Interest Group on Computer-Human Interaction (SIGCHI), 2015-03-17 |
| Learning 3D Part Assembly from a Single Image Li, Yichen; Mo, Kaichun; Shao, Lin; Sung, Minhyuk; Guibas, Leonidas, 16th European Conference on Computer Vision, ECCV 2020, pp.664 - 682, Springer Science and Business Media Deutschland GmbH, 2020-08 |
| Learning a variable-clustering strategy for octagon from labeled data generated by a static analysis Heo, Kihong; Oh, Hakjoo; Yang, Hongseok, 23rd International Symposium on Static Analysis, SAS 2016, pp.237 - 256, SAS Committee, 2016-09-08 |
| Learning Bill Similarity with Annotated and Augmented Corpora of Bills Kim, Jiseon; Oh, Alice Haeyun; Kim, In Song; Griggs, Elden, The 2021 Conference on Empirical Methods in Natural Language Processing, Empirical Methods in Natural Language Processing (EMNLP 2021), 2021-11 |
| LEARNING CONTINUOUS REPRESENTATION OF AUDIO FOR ARBITRARY SCALE SUPER RESOLUTION Kim, Jaechang; Lee, Yunjoo; Hong, Seunghoon; Ok, Jungseul, 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022, pp.3703 - 3707, Institute of Electrical and Electronics Engineers Inc., 2022-05-23 |
| Learning deconvolution network for semantic segmentation Noh, Hyeonwoo; Hong, Seunghoon; Han, Bohyung, 15th IEEE International Conference on Computer Vision, ICCV 2015, pp.1520 - 1528, IEEE Computer Society and the Computer Vision Foundation (CVF), 2015-12-10 |
| Learning Economic Indicators by Aggregating Multi-level Geospatial Information Park, Sungwon; Han, Sungwon; Ahn, Donghyun; Kim, Jaeyeon; Yang, Jaesurk; Lee, Susang; Hong, Seunghoon; et al, 36th AAAI Conference on Artificial Intelligence, AAAI 2022, pp.12053 - 12061, Association for the Advancement of Artificial Intelligence, 2022-02-22 |
| Learning Embedding of 3D models with Quadric Loss Agarwal, Nitin; Yoon, Sung-Eui; Gopi, M, 30th British Machine Vision Conference (BMVC 2019), pp.1 - 11, British Machine Vision Association (BMVA), 2019-09-10 |
| Learning fault localisation for both humans and machines using multi-objective GP Choi, Kabdo; Sohn, Jeongju; Yoo, Shin, 10th International Symposium on Search-Based Software Engineering, SSBSE 2018, pp.349 - 355, Springer Verlag, 2018-09-09 |
| Learning Feature Aggregation for Deep 3D Morphable Models Chen, Zhixiang; Kim, Tae-Kyun, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.13159 - 13168, CVF and IEEE Computer Society, 2021-06-22 |
| Learning hierarchical semantic image manipulation through structured representations Hong, Seunghoon; Yan, Xinchen; Huang, Thomas; Lee, Honglak, 32nd Conference on Neural Information Processing Systems, NeurIPS 2018, pp.2708 - 2718, Neural information processing systems foundation, 2018-12-02 |
| Learning how spectator reactions affect popularity on twitch Kim, Jeongmin; Park, Kunwoo; Song, Hyeonho; Park, Jaimie Y; Cha, Meeyoung, 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020, pp.147 - 154, Institute of Electrical and Electronics Engineers Inc., 2020-02-21 |
| Learning Low-Rank Representation for Matrix Completion Kwon, Minsu; Choi, Ho-Jin, 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020, pp.161 - 164, IEEE,Korean Institute of Information Scientists and Engineers (KIISE), 2020-02-21 |
| Learning Place Ambience from Images Using Deep ConvNet Yoon, Sanghoon; Kim, Taehun; Lee, Dongman; Hyun, Soon-Joo, 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017, pp.904 - 909, Institute of Electrical and Electronics Engineers Inc., 2017-12 |
| Learning Policy from Suboptimal Demonstrations under Transition Dynamic Mismatch Kim, Taesu; Wang, Jianhong; Antotsiou, Dafni; Kim, Tae-Kyun, Thirty-ninth International Conference on Machine Learning, Workshop on Adaptive Experimental Design and Active Learning, ICML, 2022-07-22 |
| Learning Probabilistic Models for Static Analysis Alarms Kim, Hyunsu; Raghothaman, Mukund; Heo, Kihong, The 44th ACM/IEEE International Conference on Software Engineering (ICSE 2022), pp.1282 - 1293, ACM, IEEE, 2022-05 |
| Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance Kim, Jinwoo; Hong, Seunghoon; Nguyen, Dat Tien; Suleymanzade, Ayhan; An, Hyeokjun, Thirty-seventh Conference on Neural Information Processing Systems, NeurIPS 2023, Neural Information Processing Systems Foundation, 2023-12-11 |
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