2008 |
36 | EE | 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 | EE | Jun-ichi Moribe,
Kohei Hatano,
Eiji Takimoto,
Masayuki Takeda:
Smooth Boosting for Margin-Based Ranking.
ALT 2008: 227-239 |
34 | EE | 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 | EE | 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 | EE | Marcus Hutter,
Rocco A. Servedio,
Eiji Takimoto:
Editors' Introduction.
ALT 2007: 1-8 |
30 | EE | 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 | EE | Shigeaki Harada,
Eiji Takimoto,
Akira Maruoka:
Aggregating Strategy for Online Auctions.
COCOON 2006: 33-41 |
28 | EE | Shigeaki Harada,
Eiji Takimoto,
Akira Maruoka:
Online Allocation with Risk Information.
IEICE Transactions 89-D(8): 2340-2347 (2006) |
27 | EE | Ricard Gavaldà,
Eiji Takimoto:
Foreword.
Theor. Comput. Sci. 364(1): 1-2 (2006) |
2005 |
26 | EE | Shigeaki Harada,
Eiji Takimoto,
Akira Maruoka:
Online Allocation with Risk Information.
ALT 2005: 343-355 |
2004 |
25 | EE | 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 | EE | 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 | EE | Eiji Takimoto,
Manfred K. Warmuth:
Path Kernels and Multiplicative Updates.
COLT 2002: 74-89 |
20 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | Akira Maruoka,
Eiji Takimoto:
Structured Weight-Based Prediction Algorithms.
ALT 1998: 127-142 |
9 | EE | 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 | EE | 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 | EE | 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 | EE | Eiji Takimoto,
Akira Maruoka:
Conservativeness and Monotonicity for Learning Algorithms.
COLT 1993: 377-383 |