Continual pre-training of language models Z Ke, Y Shao, H Lin, T Konishi, G Kim, B Liu arXiv preprint arXiv:2302.03241, 2023 | 54 | 2023 |
Cityprophet: City-scale irregularity prediction using transit app logs T Konishi, M Maruyama, K Tsubouchi, M Shimosaka Proceedings of the 2016 ACM International Joint Conference on Pervasive and …, 2016 | 49 | 2016 |
A theoretical study on solving continual learning G Kim, C Xiao, T Konishi, Z Ke, B Liu Advances in neural information processing systems 35, 5065-5079, 2022 | 45 | 2022 |
Early destination prediction with spatio-temporal user behavior patterns R Imai, K Tsubouchi, T Konishi, M Shimosaka Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018 | 25 | 2018 |
Learnability and algorithm for continual learning G Kim, C Xiao, T Konishi, B Liu International Conference on Machine Learning, 16877-16896, 2023 | 12 | 2023 |
Parameter-level soft-masking for continual learning T Konishi, M Kurokawa, C Ono, Z Ke, G Kim, B Liu International Conference on Machine Learning, 17492-17505, 2023 | 11 | 2023 |
Open-world continual learning: Unifying novelty detection and continual learning G Kim, C Xiao, T Konishi, Z Ke, B Liu arXiv preprint arXiv:2304.10038, 2023 | 6 | 2023 |
Multidimensional analysis of sense of agency during goal pursuit R Legaspi, W Xu, T Konishi, S Wada, Y Ishikawa Proceedings of the 30th ACM Conference on User Modeling, Adaptation and …, 2022 | 6 | 2022 |
Positing a sense of agency-aware persuasive AI: its theoretical and computational frameworks R Legaspi, W Xu, T Konishi, S Wada International Conference on Persuasive Technology, 3-18, 2021 | 6 | 2021 |
The sense of agency in human–AI interactions R Legaspi, W Xu, T Konishi, S Wada, N Kobayashi, Y Naruse, Y Ishikawa Knowledge-Based Systems 286, 111298, 2024 | 3 | 2024 |
Method and information processing apparatus that perform transfer learning while suppressing occurrence of catastrophic forgetting T Konishi, M Kurokawa, B Liu, G Kim, Z Ke US Patent App. 17/481,655, 2023 | 1 | 2023 |
Continual Learning Using Pseudo-Replay via Latent Space Sampling G Kim, S Esmaeilpour, Z Ke, T Konishi, B Liu | 1 | 2021 |
Method and information processing apparatus for performing transfer learning while suppressing occurrence of catastrophic forgetting T Konishi, M Kurokawa, B Liu, G Kim, Z Ke US Patent App. 17/939,215, 2024 | | 2024 |
Standalone effects of focus mode and social comparison functions on problematic smartphone use among adolescents T Hamamura, M Kurokawa, K Mishima, T Konishi, M Nagata, M Honjo Addictive Behaviors 147, 107834, 2023 | | 2023 |
CG-GNN: A Novel Compiled Graphs-based Feature Extraction Method for Enterprise Social Networks T Konishi, S Haruta, M Kurokawa, K Tsukatsune, Y Mizutani, T Saito, ... Proceedings of the 4th ACM Workshop on Intelligent Cross-Data Analysis and …, 2023 | | 2023 |
A Novel Graph Aggregation Method Based on Feature Distribution Around Each Ego-node for Heterophily S Haruta, T Konishi, M Kurokawa Asian Conference on Machine Learning, 452-466, 2023 | | 2023 |
Multi-view Contrastive Multiple Knowledge Graph Embedding for Knowledge Completion M Kurokawa, K Yonekawa, S Haruta, T Konishi, H Asoh, C Ono, ... 2022 21st IEEE International Conference on Machine Learning and Applications …, 2022 | | 2022 |
Continual Learning with Soft-Masking of Parameter-Level Gradient Flow T Konishi, M Kurokawa, C Ono, Z Ke, G Kim, B Liu | | 2022 |
Solving Continual Learning via Problem Decomposition G Kim, C Xiao, T Konishi, Z Ke, B Liu | | 2022 |
Partially Relaxed Masks for Knowledge Transfer Without Forgetting in Continual Learning T Konishi, M Kurokawa, C Ono, Z Ke, G Kim, B Liu Pacific-Asia Conference on Knowledge Discovery and Data Mining, 367-379, 2022 | | 2022 |