 | 2010 |
|---|
| 9 |       | Michinari Momma,
Kohei Hatano,
Hiroki Nakayama:
Ellipsoidal Support Vector Machines.
Journal of Machine Learning Research - Proceedings Track 13: 31-46 (2010) |
| 2009 |
|---|
| 8 | | Ryohei Fujimaki,
Satoshi Morinaga,
Michinari Momma,
Kenji Aoki,
Takayuki Nakata:
Linear Time Model Selection for Mixture of Heterogeneous Components.
ACML 2009: 82-97 |
| 7 | | Michinari Momma,
Satoshi Morinaga,
Daisuke Komura:
Promoting Total Efficiency in Text Clustering via Iterative and Interactive Metric Learning.
ICDM 2009: 878-883 |
| 2005 |
|---|
| 6 | | Michinari Momma:
Efficient computations via scalable sparse kernel partial least squares and boosted latent features.
KDD 2005: 654-659 |
| 2003 |
|---|
| 5 | | Tijl De Bie,
Michinari Momma,
Nello Cristianini:
Efficiently Learning the Metric with Side-Information.
ALT 2003: 175-189 |
| 4 | | Michinari Momma,
Kristin P. Bennett:
Sparse Kernel Partial Least Squares Regression.
COLT 2003: 216-230 |
| 3 | | Joel Carleton,
Daragh Hartnett,
Joseph Milana,
Michinari Momma,
Joseph Sirosh,
Gabriela Surpi:
Model Builder for Predictive Analytics & Fair Isaac's approach to KDD Cup 2003.
SIGKDD Explorations 5(2): 163-164 (2003) |
| 2002 |
|---|
| 2 | | Kristin P. Bennett,
Michinari Momma,
Mark J. Embrechts:
MARK: a boosting algorithm for heterogeneous kernel models.
KDD 2002: 24-31 |
| 1 | | Michinari Momma,
Kristin P. Bennett:
A Pattern Search Method for Model Selection of Support Vector Regression.
SDM 2002 |
Data released under the ODC-BY 1.0 license — See also our legal information page