Showing results 120861 to 120880 of 279409
Learning to generate proactive and reactive behavior using a dynamic neural network model with time-varying variance prediction mechanism Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya; Sugano, Shigeki; Tani, Jun, ADVANCED ROBOTICS, v.28, no.17, pp.1189 - 1203, 2014-10 |
Learning to Generate Questions by Learning to Recover Answer-containing Sentences Back, Seohyun; Keida, Akhil; Chinthakindi, Sai Chetan; Lee, Haejun; Choo, Jaegul, The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Association for Computational Linguistics (ACL), 2021-08-02 |
Learning to generate semantic layouts for higher text-image correspondence in text-to-image synthesis = 문자열 기반 이미지 생성 시 높은 문자열 반영도를 위한 의미론적 분할 지도 동시 생성 기법link Park, Minho; 박민호; et al, 한국과학기술원, 2024 |
Learning to guide task and motion planning using score-space representation Kim, Beomjoon; Wang, Zi; Kaelbling, Leslie Pack; Lozano-Perez, Tomas, INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, v.38, no.7, pp.793 - 812, 2019-05 |
Learning to jump over a hurdle with a quadruped robot using reinforcement learning = 강화학습을 이용한 사족보행로봇의 장애물 뛰어넘기 학습link 흐첼 야콥; Hwangbo, Jemin; et al, 한국과학기술원, 2023 |
Learning to lip read words by watching videos Chung, Joon Son; Zisserman, Andrew, COMPUTER VISION AND IMAGE UNDERSTANDING, v.173, pp.76 - 85, 2018-08 |
Learning to Localize Sound Source in Visual Scenes SENOCAK, Arda; Oh, Tae-Hyun; Kim, Junsik; Yang, Ming-Hsuan; Kweon, In-So, 31st IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.4358 - 4366, IEEE Computer Society and the Computer Vision Foundation (CVF), 2018-06-20 |
Learning to Localize Sound Sources in Visual Scenes: Analysis and Applications Senocak, Arda; Oh, Tae-Hyun; Kim, Junsik; Yang, Ming-Hsuan; Kweon, In-So, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, v.43, no.5, pp.1605 - 1619, 2021-05 |
Learning to Maximize Speech Quality Directly Using MOS Prediction for Neural Text-to-Speech Choi, Yeunju; Jung, Youngmoon; Suh, Youngjoo; Kim, Hoi-Rin, IEEE ACCESS, v.10, pp.52621 - 52629, 2022-05 |
Learning to Perceive the World as Probabilistic or Deterministic via Interaction With Others: A Neuro-Robotics Experiment Murata, Shingo; Yamashita, Yuichi; Arie, Hiroaki; Ogata, Testsuya; Sugano, Shigeki; Tani, Jun, IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, v.28, no.4, pp.830 - 848, 2017-04 |
Learning to perturb word embeddings for out-of-distribution QA Lee, Seanie; Kang, Minki; Lee, Juho; Hwang, Sung Ju, The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Association for Computational Linguistics (ACL) and Asian Federation of Natural Language Processing (AFNLP), 2021-08-02 |
Learning to propagate labels: Transductive propagation network for few-shot learning Liu, Yanbin; Lee, Juho; Park, Minseop; Kim, Saehoon; Yang, Eunho; Hwang, Sung Ju; Yang, Yi, 7th International Conference on Learning Representations, ICLR 2019, International Conference on Learning Representations, ICLR, 2019-05-06 |
Learning to Quantize Deep Networks by Optimizing Quantization Intervals with Task Loss Jung Sang Gil; Son, Cahng Tong; Lee, Seo Hyung; Son, Jin Woo; Kwak, Young Jun; Han, Jae Joon; Hwang, Sung Ju; et al, 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.1 - 10, Conference on Computer Vision and Pattern Recognition(CVPR), 2019-06-16 |
Learning to reach into the unknown: Selecting initial conditions when reaching in clutter Park, Daehyung; Kapusta, Ariel; Kim, You Keun; Rehg, James M.; Kemp, Charles C., 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014, pp.630 - 637, IEEE Robotics and Automation Society (RAS), 2014-09 |
Learning to Recommend Visualizations from Data Qian, Xin; Rossi, Ryan A.; Du, Fan; Kim, Sungchul; Koh, Eunyee; Malik, Sana; Lee, Tak Yeon; et al, 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021, pp.1359 - 1369, Association for Computing Machinery, 2021-08 |
Learning to Reconstruct HDR Images from Events, with Applications to Depth and Flow Prediction Mostafavi, Mohammad; Wang, Lin; Yoon, Kuk-Jin, INTERNATIONAL JOURNAL OF COMPUTER VISION, v.129, no.4, pp.900 - 920, 2021-04 |
Learning to Reproduce Fluctuating Behavioral Sequences Using a Dynamic Neural Network Model with Time-Varying Variance Estimation Mechanism Tani, Jun; Murata, Shingo; Namikawa, J; Arie, H; Sugano, H, The Third Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, pp.1 - 6, IEEE, 2013-08-22 |
Learning to Reproduce Fluctuating Time Series by Inferring Their Time-Dependent Stochastic Properties: Application in Robot Learning Via Tutoring Murata, Shingo; Namikawa, Jun; Arie, Hiroaki; Sugano, Shigeki; Tani, Jun, IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT, v.5, no.4, pp.298 - 310, 2013-12 |
Learning to reproduce stochastic time series using stochastic LSTM Gulshad, Sadaf; Sigmund, Dick; Kim, Jong-Hwan, Neural Networks (IJCNN), 2017 International Joint Conference on, IEEE, 2017-05-14 |
Learning to Sample with Local and Global Contexts in Experience Replay Buffers Oh, Youngmin; Lee, Kimin; Shin, Jinwoo; Yang, Eunho; Hwang, Sung Ju, The Ninth International Conference on Learning Representations (ICLR), International Conference on Learning Representations (ICLR), 2021-05-04 |
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