 | 2009 |
|---|
| 39 |       | Kohei Hatano,
Eiji Takimoto:
Linear Programming Boosting by Column and Row Generation.
Discovery Science 2009: 401-408 |
| 38 | | Kei Uchizawa,
Takao Nishizeki,
Eiji Takimoto:
Energy Complexity and Depth of Threshold Circuits.
FCT 2009: 335-345 |
| 37 | | Kei Uchizawa,
Takao Nishizeki,
Eiji Takimoto:
Size and Energy of Threshold Circuits Computing Mod Functions.
MFCS 2009: 724-735 |
| 2008 |
|---|
| 36 | | Eiji Takimoto,
Yoshihisa Kondo,
Satoko Itaya,
Ryutaro Suzuki,
Sadao Obana:
Evaluation of Multi-Channel Flooding for Inter-Vehicle Communication.
AINA Workshops 2008: 960-965 |
| 35 | | Jun-ichi Moribe,
Kohei Hatano,
Eiji Takimoto,
Masayuki Takeda:
Smooth Boosting for Margin-Based Ranking.
ALT 2008: 227-239 |
| 34 | | Takayuki Sato,
Kazuyuki Amano,
Eiji Takimoto,
Akira Maruoka:
Monotone DNF Formula That Has a Minimal or Maximal Number of Satisfying Assignments.
COCOON 2008: 191-203 |
| 33 | | Kei Uchizawa,
Eiji Takimoto:
Exponential lower bounds on the size of constant-depth threshold circuits with small energy complexity.
Theor. Comput. Sci. 407(1-3): 474-487 (2008) |
| 2007 |
|---|
| 32 |  | Marcus Hutter,
Rocco A. Servedio,
Eiji Takimoto:
Algorithmic Learning Theory, 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings
Springer 2007 |
| 31 | | Marcus Hutter,
Rocco A. Servedio,
Eiji Takimoto:
Editors' Introduction.
ALT 2007: 1-8 |
| 30 | | Kei Uchizawa,
Eiji Takimoto:
An Exponential Lower Bound on the Size of Constant-Depth Threshold Circuits with Small Energy Complexity.
IEEE Conference on Computational Complexity 2007: 169-178 |
| 2006 |
|---|
| 29 | | Shigeaki Harada,
Eiji Takimoto,
Akira Maruoka:
Aggregating Strategy for Online Auctions.
COCOON 2006: 33-41 |
| 28 | | Shigeaki Harada,
Eiji Takimoto,
Akira Maruoka:
Online Allocation with Risk Information.
IEICE Transactions 89-D(8): 2340-2347 (2006) |
| 27 | | Ricard Gavaldà,
Eiji Takimoto:
Foreword.
Theor. Comput. Sci. 364(1): 1-2 (2006) |
| 2005 |
|---|
| 26 | | Shigeaki Harada,
Eiji Takimoto,
Akira Maruoka:
Online Allocation with Risk Information.
ALT 2005: 343-355 |
| 2004 |
|---|
| 25 | | Eiji Takimoto,
Syuhei Koya,
Akira Maruoka:
Boosting Based on Divide and Merge.
ALT 2004: 127-141 |
| 2003 |
|---|
| 24 | | Ricard Gavaldà,
Klaus P. Jantke,
Eiji Takimoto:
Algorithmic Learning Theory, 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings
Springer 2003 |
| 23 | | Eiji Takimoto,
Manfred K. Warmuth:
Path Kernels and Multiplicative Updates.
Journal of Machine Learning Research 4: 773-818 (2003) |
| 22 | | Eiji Takimoto,
Akira Maruoka:
Top-down decision tree learning as information based boosting.
Theor. Comput. Sci. 292(2): 447-464 (2003) |
| 2002 |
|---|
| 21 | | Eiji Takimoto,
Manfred K. Warmuth:
Path Kernels and Multiplicative Updates.
COLT 2002: 74-89 |
| 20 | | Akira Maruoka,
Eiji Takimoto:
On-Line Algorithm to Predict Nearly as Well as the Best Pruning of a Decision Tree.
Progress in Discovery Science 2002: 296-306 |
| 19 | | Eiji Takimoto,
Akira Maruoka:
Top-Down Decision Tree Boosting and Its Applications.
Progress in Discovery Science 2002: 327-337 |
| 18 | | Eiji Takimoto,
Manfred K. Warmuth:
Predicting nearly as well as the best pruning of a planar decision graph.
Theor. Comput. Sci. 288(2): 217-235 (2002) |
| 2001 |
|---|
| 17 | | Eiji Takimoto,
Akira Maruoka,
Volodya Vovk:
Predicting nearly as well as the best pruning of a decision tree through dynamic programming scheme.
Theor. Comput. Sci. 261(1): 179-209 (2001) |
| 2000 |
|---|
| 16 | | Eiji Takimoto,
Manfred K. Warmuth:
The Last-Step Minimax Algorithm.
ALT 2000: 279-290 |
| 15 | | Eiji Takimoto,
Manfred K. Warmuth:
The Minimax Strategy for Gaussian Density Estimation. pp.
COLT 2000: 100-106 |
| 14 | | Jun Mizuno,
Tasuya Watanabe,
Kazuya Ueki,
Kazuyuki Amano,
Eiji Takimoto,
Akira Maruoka:
On-Line Estimation of Hidden Markov Model Parameters.
Discovery Science 2000: 155-169 |
| 13 | | Eiji Takimoto,
Yoshifumi Sakai,
Akira Maruoka:
The learnability of exclusive-or expansions based on monotone DNF formulas.
Theor. Comput. Sci. 241(1-2): 37-50 (2000) |
| 1999 |
|---|
| 12 | | Eiji Takimoto,
Manfred K. Warmuth:
Predicting Nearly as well as the best Pruning of a Planar Decision Graph.
ATL 1999: 335-346 |
| 11 | | Yoshifumi Sakai,
Eiji Takimoto,
Akira Maruoka:
Proper Learning Algorithm for Functions of k Terms under Smooth Distributions.
Inf. Comput. 152(2): 188-204 (1999) |
| 1998 |
|---|
| 10 | | Akira Maruoka,
Eiji Takimoto:
Structured Weight-Based Prediction Algorithms.
ALT 1998: 127-142 |
| 9 | | Eiji Takimoto,
Akira Maruoka:
On the Boosting Algorithm for Multiclass Functions Based on Information-Theoretic Criterion for Approxiamtion.
Discovery Science 1998: 256-267 |
| 1997 |
|---|
| 8 | | Eiji Takimoto,
Ken'ichi Hirai,
Akira Maruoka:
A Simple Algorithm for Predicting Nearly as Well as the Best Pruning Labeled with the Best Prediction Values of a Decision Tree.
ALT 1997: 385-400 |
| 7 | | Eiji Takimoto,
Akira Miyashiro,
Akira Maruoka,
Yoshifumi Sakai:
Learning Orthogonal F-Horn Formulas.
Theor. Comput. Sci. 185(1): 177-190 (1997) |
| 1996 |
|---|
| 6 | | Eiji Takimoto,
Yoshifumi Sakai,
Akira Maruoka:
Learnability of Exclusive-Or Expansion Based on Monotone DNF Formulas.
ALT 1996: 12-25 |
| 1995 |
|---|
| 5 | | Akira Miyashiro,
Eiji Takimoto,
Yoshifumi Sakai,
Akira Maruoka:
Learning Orthogonal F-Horn Formulas.
ALT 1995: 110-122 |
| 4 | | Yoshifumi Sakai,
Eiji Takimoto,
Akira Maruoka:
Proper Learning Algorithm for Functions of k Terms Under Smooth Distributions.
COLT 1995: 206-213 |
| 1994 |
|---|
| 3 | | Eiji Takimoto,
Ichiro Tajika,
Akira Maruoka:
Mutual Information Gaining Algorithm and Its Relation to PAC-Learning Algorithm.
AII/ALT 1994: 547-559 |
| 1993 |
|---|
| 2 | | Eiji Takimoto,
Akira Maruoka:
On the Sample Complexity of Consistent Learning with One-Sided Error.
ALT 1993: 265-278 |
| 1 | | Eiji Takimoto,
Akira Maruoka:
Conservativeness and Monotonicity for Learning Algorithms.
COLT 1993: 377-383 |
