| |
| 2007 | ||
|---|---|---|
| 8 | EE | Takafumi Kanamori: Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability. ALT 2007: 358-372 |
| 7 | EE | Takafumi Kanamori: Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability. IEICE Transactions 90-D(12): 2033-2042 (2007) |
| 6 | EE | Takafumi Kanamori: Pool-based active learning with optimal sampling distribution and its information geometrical interpretation. Neurocomputing 71(1-3): 353-362 (2007) |
| 2006 | ||
| 5 | EE | Takafumi Kanamori, Ichiro Takeuchi: Conditional mean estimation under asymmetric and heteroscedastic error by linear combination of quantile regressions. Computational Statistics & Data Analysis 50(12): 3605-3618 (2006) |
| 2004 | ||
| 4 | EE | Takafumi Kanamori, Takashi Takenouchi, Shinto Eguchi, Noboru Murata: The Most Robust Loss Function for Boosting. ICONIP 2004: 496-501 |
| 3 | EE | Noboru Murata, Takashi Takenouchi, Takafumi Kanamori, Shinto Eguchi: Information Geometry of U-Boost and Bregman Divergence. Neural Computation 16(7): 1437-1481 (2004) |
| 2002 | ||
| 2 | EE | Takafumi Kanamori: A New Sequential Algorithm for Regression Problems by Using Mixture Distribution. ICANN 2002: 535-540 |
| 1 | EE | Ichiro Takeuchi, Yoshua Bengio, Takafumi Kanamori: Robust Regression with Asymmetric Heavy-Tail Noise Distributions. Neural Computation 14(10): 2469-2496 (2002) |
| 1 | Yoshua Bengio | [1] |
| 2 | Shinto Eguchi | [3] [4] |
| 3 | Noboru Murata | [3] [4] |
| 4 | Takashi Takenouchi | [3] [4] |
| 5 | Ichiro Takeuchi | [1] [5] |