| 2007 |
|---|
| 9 | EE | Takafumi Kanamori:
Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability.
ALT 2007: 358-372 |
| 8 | EE | Takafumi Kanamori:
Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability.
IEICE Transactions 90-D(12): 2033-2042 (2007) |
| 7 | EE | Takafumi Kanamori:
Pool-based active learning with optimal sampling distribution and its information geometrical interpretation.
Neurocomputing 71(1-3): 353-362 (2007) |
| 2006 |
|---|
| 6 | 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) |
| 5 | EE | Takafumi Kanamori,
Takashi Takenouchi,
Noboru Murata:
Geometrical Structure of Boosting Algorithm.
New Generation Comput. 25(1): 117-141 (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) |
