| Comparison of algorithms that select features for pattern classifiers M Kudo, J Sklansky Pattern recognition 33 (1), 25-41, 2000 | 1242 | 2000 |
| Multidimensional curve classification using passing-through regions M Kudo, J Toyama, M Shimbo Pattern Recognition Letters 20 (11-13), 1103-1111, 1999 | 187 | 1999 |
| Partitioning of web graphs by community topology H Ino, M Kudo, A Nakamura Proceedings of the 14th international conference on World Wide Web, 661-669, 2005 | 124 | 2005 |
| Algorithms for adversarial bandit problems with multiple plays T Uchiya, A Nakamura, M Kudo International Conference on Algorithmic Learning Theory, 375-389, 2010 | 112 | 2010 |
| Performance analysis of minimum/spl lscr//sub 1/-norm solutions for underdetermined source separation I Takigawa, M Kudo, J Toyama IEEE transactions on signal processing 52 (3), 582-591, 2004 | 109 | 2004 |
| Privacy-preserved behavior analysis and fall detection by an infrared ceiling sensor network S Tao, M Kudo, H Nonaka Sensors 12 (12), 16920-16936, 2012 | 93 | 2012 |
| Sitting posture analysis by pressure sensors K Kamiya, M Kudo, H Nonaka, J Toyama 2008 19th International Conference on Pattern Recognition, 1-4, 2008 | 82 | 2008 |
| Non-parametric classifier-independent feature selection N Abe, M Kudo Pattern recognition 39 (5), 737-746, 2006 | 62 | 2006 |
| A comparative evaluation of medium-and large-scale feature selectors for pattern classifiers M Kudo, J Sklansky Kybernetika 34 (4), [429]-434, 1998 | 54 | 1998 |
| VHP: approximate nearest neighbor search via virtual hypersphere partitioning K Lu, H Wang, W Wang, M Kudo Proceedings of the VLDB Endowment 13 (9), 1443-1455, 2020 | 53 | 2020 |
| MDL-based selection of the number of components in mixture models for pattern classification H Tenmoto, M Kudo, M Shimbo Advances in Pattern Recognition: Joint IAPR International Workshops SSPR'98 …, 1998 | 51 | 1998 |
| A fast hierarchical alternating least squares algorithm for orthogonal nonnegative matrix factorization K Kimura, Y Tanaka, M Kudo Asian Conference on Machine Learning, 129-141, 2015 | 50 | 2015 |
| Entropy criterion for classifier-independent feature selection N Abe, M Kudo International Conference on Knowledge-Based and Intelligent Information and …, 2005 | 49 | 2005 |
| Segmentation of pores in wood microscopic images based on mathematical morphology with a variable structuring element S Pan, M Kudo Computers and Electronics in Agriculture 75 (2), 250-260, 2011 | 47 | 2011 |
| Multi-label classification with meta-label-specific features L Sun, M Kudo, K Kimura 2016 23rd International conference on pattern recognition (ICPR), 1612-1617, 2016 | 44 | 2016 |
| Efficient action recognition via local position offset of 3D skeletal body joints G Lu, Y Zhou, X Li, M Kudo Multimedia Tools and Applications 75, 3479-3494, 2016 | 41 | 2016 |
| Construction of class regions by a randomized algorithm: A randomized subclass method M Kudo, S Yanagi, M Shimbo Pattern Recognition 29 (4), 581-588, 1996 | 41 | 1996 |
| Data compression by volume prototypes for streaming data K Tabata, M Sato, M Kudo Pattern Recognition 43 (9), 3162-3176, 2010 | 39 | 2010 |
| R2LSH: A nearest neighbor search scheme based on two-dimensional projected spaces K Lu, M Kudo 2020 IEEE 36th International Conference on Data Engineering (ICDE), 1045-1056, 2020 | 36 | 2020 |
| Multiperson locating and their soft tracking in a binary infrared sensor network S Tao, M Kudo, BN Pei, H Nonaka, J Toyama IEEE Transactions on Human-Machine Systems 45 (5), 550-561, 2014 | 36 | 2014 |
Atsuyoshi NakamuraHokkaido UniversityBestätigte E-Mail-Adresse bei ist.hokudai.ac.jp
