Browse "Kim Jaechul Graduate School of AI(김재철AI대학원)" by Type Conference
Showing results 275 to 334 of 578
| K-centered Patch Sampling for Efficient Video Recognition Park, Seong Hyeon; Tack, Jihoon; Heo, Byeongho; Ha, Jung-Woo; Shin, Jinwoo, 17th European Conference on Computer Vision (ECCV), pp.160 - 176, SPRINGER INTERNATIONAL PUBLISHING AG, 2022-10 |
| K-Hairstyle: A Large-Scale Korean Hairstyle Dataset for Virtual Hair Editing and Hairstyle Classification Kim, Taewoo; Chung, Chaeyeon; Park, Sunghyun; Gu, Gyojung; Nam, Keonmin; Choe, Wonzo; Lee, Jaesung; et al, 2021 IEEE International Conference on Image Processing(ICIP), pp.1299 - 1303, ICIP, 2021-09-22 |
| KALA: Knowledge-Augmented Language Model Adaptation Kang, Minki; Baek, Jinheon; Hwang, Sung Ju, 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022, pp.5144 - 5167, Association for Computational Linguistics (ACL), 2022-07-12 |
| KILT: a Benchmark for Knowledge Intensive Language Tasks Petroni, Fabio; Piktus, Aleksandra; Fan, Angela; Lewis, Patrick; Yazdani, Majid; De Cao, Nicola; Thorne, James; et al, 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2021, pp.2523 - 2544, Association for Computational Linguistics (ACL), 2021-06-10 |
| KNOW YOUR ACTION SET: LEARNING ACTION RELATIONS FOR REINFORCEMENT LEARNING Jain, Ayush; Kosaka, Norio; Kim, Kyung-Min; Lim, Joseph Jaewhan, 10th International Conference on Learning Representations, ICLR 2022, International Conference on Learning Representations, ICLR, 2022-04 |
| Knowledge Corpus Error in Question Answering Lee, Yejoon; Oh, Philhoon; Thorne, James, Empirical Methods in Natural Language Processing, EMNLP 2023, Association for Computational Linguistics, 2023-12-08 |
| Knowledge Unlearning for Mitigating Privacy Risks in Language Models Jang, Joel; Yoon, Dongkeun; Yang, Sohee; Cha, Sungmin; Lee, Moontae; Logeswaran, Lajanugen; Seo, Minjoon, ACL 2023, pp.14389 - 14408, Association for Computational Linguistics (ACL), 2023-07 |
| Knowledge-Augmented Language Model Verification Baek, Jinheon; Jeong, Soyeong; Kang, Minki; Park, Jong-Cheol; Hwang, Sung Ju, The 2023 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics (ACL), 2023-12-07 |
| Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks Kang, Minki; Lee, Seanie; Baek, Jinheon; Kenji, Kawaguchi; Hwang, Sung Ju, 37th Conference on Neural Information Processing Systems, NeurIPS 2023, Neural Information Processing Systems Foundatio, 2023-12-14 |
| L0-compressed sensing for parallel dynamic MRI using sparse Bayesian learning Jung, H; Yoon, HS; Ye, Jong Chul, IEEE International Symposium on Biomedical Imaging (ISBI), IEEE, 2011-03 |
| Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning Kim, Junsu; Seo, Younggyo; Shin, Jinwoo, 35th Conference on Neural Information Processing Systems, NeurIPS 2021, Neural Information Processing Systems, 2021-12-07 |
| Language Detoxification with Attribute-Discriminative Latent Space Kwak, Jin Myung; Kim, Minseon; Hwang, Sung Ju, 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023, pp.10149 - 10171, Association for Computational Linguistics (ACL), 2023-07-11 |
| Large Language Models Are Reasoning Teachers Ho, Namgyu; Schmid, Laura; Yun, Seyoung, 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023, pp.14852 - 14882, Association for Computational Linguistics (ACL), 2023-07-10 |
| Large-scale log-determinant computation through stochastic Chebyshev expansions Han, Insu; Malioutov, Dmitry; Shin, Jinwoo, ICML 2015, International Machine Learning Society (IMLS), 2015-07-07 |
| Large-Scale Meta-Learning with Continual Trajectory Shifting Shin, Jae Woong; Lee, Hae Beom; Gong, Boqing; Hwang, Sung Ju, 38th International Conference on Machine Learning, ICML 2021, International Machine Learning Society, 2021-07-18 |
| Learning based utility maximization for multi-resource management Lee, DongHoon; Chong, Song, 13th International Conference on Future Internet Technologies, CFI 2018, Association for Computing Machinery, 2018-06 |
| Learning Bounds for Risk-sensitive Learning Lee, Jaeho; Park, Sejun; Shin, Jinwoo, 34th Conference on Neural Information Processing Systems (NeurIPS) 2020, Neural Information Processing Systems, 2020-12-07 |
| Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior Tong, Anh; Tran, Toan; Bui, Hung; Choi, Jaesik, AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2021-02-05 |
| Learning Fractional White Noises in Neural Stochastic Differential Equations Tong, Anh Hoan; Nguyen-Tang, Thanh; Tran, Toan; Choi, Jaesik, 36th Conference on Neural Information Processing Systems, NeurIPS 2022, Neural Information Processing Systems Foundation, 2022-12-01 |
| Learning from Better Supervision: Self-distillation for Learning with Noisy Labels Baek, Kyungjune; Lee, Seungho; Shim, Hyunjung, 26th International Conference on Pattern Recognition / 8th International Workshop on Image Mining - Theory and Applications (IMTA), pp.1829 - 1835, IEEE, 2022-08-23 |
| Learning How Long to Wait: Adaptively-Constrained Monotonic Multihead Attention for Streaming ASR Song, Jaeyun; Shim, Hajin; Yang, Eunho, 2021 IEEE Automatic Speech Recognition and Understanding Workshop, ASRU 2021, pp.441 - 448, Institute of Electrical and Electronics Engineers Inc., 2021-12-15 |
| Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance Kim, Yoonjeon; Kim, Hyunsu; Kim, Junho; Choi, Yunjey; Yang, Eunho, The Eleventh International Conference on Learning Representations, ICLR 2023, The International Conference on Learning Representations, 2023-05-03 |
| Learning Task Clusters via Sparsity Grouped Multitask Learning Kshirsagar, Meghana; Yang, Eunho; Lozano, Aurélie C, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2017, pp.673 - 689, Springer Verlag, 2017-09 |
| Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction Baek, Jinheon; Lee, Dong Bok; Hwang, Sung Ju, Thirty-fourth Conference on Neural Information Processing Systems, NeurIPS 2020, NeurIPS, 2020-12-06 |
| Learning to Generate Inversion-Resistant Model Explanations Jeong, Hoyong; Lee, Suyoung; Hwang, Sung Ju; Son, Sooel, 36th Annual Conference on Neural Information Processing Systems (NeurIPS 2022), NeurIPS, 2022-11-30 |
| 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 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 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 |
| Learning to Specialize with Knowledge Distillation for Visual Question Answering Mun, Jonghwan; Lee, Kimin; Shin, Jinwoo; Han, Bohyung, 32nd Conference on Neural Information Processing Systems (NIPS), NEURAL INFORMATION PROCESSING SYSTEMS (NIPS), 2018-12-04 |
| Learning What and Where to Transfer Jang, Yunhun; Lee, Hankook; Hwang, Sung Ju; Shin, Jinwoo, 36th International Conference on Machine Learning (ICML), ICML committee, 2019-06-13 |
| Linear attention is (maybe) all you need (to understand Transformer optimization) Ahn, Kwangjun; Cheng, Xiang; Song, Minhak; Yun, Chulhee; Jadbabaie, Ali; Sra, Suvrit, 12th International Conference on Learning Representations, ICLR 2024, International Conference on Learning Representations (ICLR), 2024-05-07 |
| LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation Kim, Geon-Hyeong; Lee, Jongmin; Jang, Youngsoo; Yang, Hongseok; Kim, Kee-Eung, The 36th Conference on Neural Information Processing Systems (NeurIPS 2022), Neural information processing systems foundation, 2022-12-01 |
| Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions Lee, Haanvid; Jongmin Lee; choi, yunseon; Wonseok Jeon; Byung-Jun Lee; Yung-Kyun Noh; Kim, Kee-Eung, 36th Conference on Neural Information Processing Systems, NeurIPS 2022, Advances in Neural Information Processing Systems, 2022-09-14 |
| Logit Mixing Training for More Reliable and Accurate Prediction Bang, Duhyeon; Baek, Kyungjune; Kim, Jiwoo; Jeon, Yunho; Kim, Jin-Hwa; Kim, Jiwon; Lee, Jongwuk; et al, 31st International Joint Conference on Artificial Intelligence, IJCAI 2022, pp.2812 - 2819, International Joint Conferences on Artificial Intelligence, 2022-07-25 |
| Long-tail Mixup for Extreme Multi-label Classification Han, Sangwoo; Choi, Eunseong; Lim, Chan; Shim, Hyunjung; Lee, Jongwuk, 31st ACM International Conference on Information and Knowledge Management, CIKM 2022, pp.3998 - 4002, Association for Computing Machinery, 2022-10 |
| Making 802.11 DCF Near-Optimal: Design, Implementation, and Evaluation Lee, Jinsung; Lee, Hojin; Yi, Yung; Chong, Song; Nardelli, Bruno; Chaing, Mung, IEEE SECON 2013, pp.86 - 94, IEEE, 2013-06-25 |
| MAP inference for Bayesian inverse reinforcement learning Choi, Jae-Deug; Kim, Kee-Eung, 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011, Neural Information Processing Systems Foundation, 2011-12 |
| Margin-based Neural Network Watermarking Kim, Byungjoo; Lee, Suyoung; Lee, Seanie; Son, Sooel; Hwang, Sung Ju, 40th International Conference on Machine Learning (ICML 2023), Proceedings of Machine Learning Research, 2023-07-23 |
| MARIO: Modality-Aware Attention and Modality-Preserving Decoders for Multimedia Recommendation Kim, Taeri; Lee, Yeon-Chang; Shin, Kijung; Kim, Sang-Wook, 31st ACM International Conference on Information and Knowledge Management, CIKM 2022, pp.993 - 1002, Association for Computing Machinery, 2022-10-18 |
| Martingale posterior neural processes Lee, Hyungi; Yun, Eunggu; Nam, Giung; Fong, E; Lee, Juho, The Eleventh International Conference on Learning Representations, International Conference on Learning Representations, 2023-05-01 |
| Masked World Models for Visual Control Seo, Younggyo; Hafner, Danijar; Liu, Hao; Liu, Fangchen; James, Stephen; Lee, Kimin; Abbeel, Pieter, 6th Conference on Robot Learning, CoRL 2022, pp.1332 - 1344, ML Research Press, 2022-12-17 |
| MASKER: Masked Keyword Regularization for Reliable Text Classification Moon, Seung Jun; Mo, Sangwoo; Lee, Kimin; Lee, Jaeho; Shin, Jinwoo, 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence, pp.13578 - 13586, ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE, 2021-02-06 |
| Max-contribution: On optimal resource allocation in delay tolerant networks Lee, Kyunghan; Yi, Yung; Jeong, Jaeseong; Won, Hyungsuk; Rhee, Injong; Chong, Song, IEEE INFOCOM 2010, pp.1 - 9, IEEE, 2010-03-14 |
| Max-min resource allocation in a network processor Yi, Sang-Yoon; Shin, Minsu; Kim, Junsung; Shrestha Sachin Lal; Chong, Song, IEEE GLOBECOM 2004, pp.582 - 588, IEEE, 2004-11-29 |
| Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization Shin, Jinwoo; Park, Sejun, UAI 2015, Association for Uncertainty in Artificial Intelligence, 2015-07-14 |
| Memory Heat Map: Anomaly Detection in Real-Time Embedded Systems Using Memory Behavior Yoon, Man-Ki; Mohan, Sibin; Choi, Jaesik; Sha, Lui, The 52nd ACM/EDAC/IEEE Design Automation Conference (DAC 2015), pp.1 - 6, ACM Special Interest Group on Design Automation (SIGDA), 2015-06-09 |
| Meta learning low rank covariance factors for energy-based deterministic uncertainty Willette, Jeffrey Ryan; Lee, Hae Beom; Lee, Juho; Hwang, Sung Ju, Tenth International Conference on Learning Representations, International Conference on Learning Representations, 2022-04-27 |
| Meta Variance Transfer: Learning to Augment from The Others Park, Seong-Jin; Han, Seungju; Baek, Jiwon; Kim, Insoo; Song, Juhwan; Lee, Hae Beom; Han, Jae-Joon; et al, 37th International Conference on Machine Learning, ICML 2020, pp.7466 - 7476, ICML, 2020-07-13 |
| Meta-Learning for Online Update of Recommender Systems Kim, MinSeok; Song, Hwanjun; Shin, Yooju; Park, Dongmin; Shin, Kijung; Lee, Jae-Gil, 36th AAAI Conference on Artificial Intelligence, AAAI 2022, pp.4065 - 4074, Association for the Advancement of Artificial Intelligence, 2022-02-25 |
| Meta-Learning with Self-Improving Momentum Target Tack, Jihoon; Park, Jongjin; Lee, Hankook; Lee, Jaeho; Shin, Jinwoo, 36th Conference on Neural Information Processing Systems, NeurIPS 2022, Neural information processing systems foundation, 2022-11 |
| Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets Lee, Hayeon; An, Sohyung; Kim, Minseon; Hwang, Sung Ju, The Eleventh International Conference on Learning Representations, ICLR 2023, International Conference on Learning Representations, 2023-05-01 |
| MGGAN: Solving Mode Collapse Using Manifold-Guided Training Bang, Duhyeon; Shim, Hyunjung, 18th IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021, pp.2347 - 2356, Institute of Electrical and Electronics Engineers Inc., 2021-10 |
| MiDaS: Representative Sampling from Real-world Hypergraphs Choe, Min Young; Yoo, Jaemin; Lee, Geon; Baek, Woonsung; Kang, U; Shin, Kijung, 31st ACM World Wide Web Conference, WWW 2022, pp.1080 - 1092, Association for Computing Machinery, Inc, 2022-04-25 |
| Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond Yun, Chulhee; Rajput, Shashank; Sra, Suvrit, 10th International Conference on Learning Representations, ICLR 2022, International Conference on Learning Representations (ICLR), 2022-04-26 |
| Minimizing Trajectory Curvature of ODE-based Generative Models Lee, Sangyun; Kim, Beomsu; Ye, Jong Chul, 40th International Conference on Machine Learning, ICML 2023, International Machine Learning Society (IMLS), 2023-07 |
| Minimum Weight Perfect Matching via Blossom Belief Propagation Ahn, Sungsoo; Park, Sejun; Misha Chertkov; Shin, Jinwoo, NIPS 2015, Neural Information Processing Systems Foundation, 2015-12-08 |
| Mining GOLD Samples for Conditional GANs Mo, Sangwoo; Kim, Chiheon; Kim, Sungwoong; Cho, Minsu; Shin, Jinwoo, 33rd Conference on Neural Information Processing Systems (NeurIPS), NIPS committee, 2019-12-10 |
| Mining of Real-world Hypergraphs: Patterns, Tools, and Generators Lee, Geon; Yoo, Jaemin; Shin, Kijung, 31st ACM International Conference on Information and Knowledge Management, CIKM 2022, pp.5144 - 5147, Association for Computing Machinery, 2022-10-19 |
| Mining of Real-world Hypergraphs: Patterns, Tools, and Generators Lee, Geon; Yoo, Jaemin; Shin, Kijung, 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, pp.5811 - 5812, Association for Computing Machinery, 2023-08-06 |
| Mitigating Dataset Bias by Using Per-Sample Gradient Ahn, Sumyeong; Kim, SeongYoon; Yun, Seyoung, Eleventh International Conference on Learning Representations, ICLR 2023, International Conference on Learning Representations, 2023-05-02 |
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