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Eiji Takimoto
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2020 – today
- 2024
- [j34]Zhiyi Zhu
, Eiji Takimoto
, Patrick Finnerty
, Chikara Ohta
:
A CQI and Hysteretic-Based Decision Algorithm to Prevent Handover Failures for Pedestrian Mobility in Mobile Communication HetNet. IEEE Access 12: 92348-92367 (2024) - [j33]Yiping Tang, Kohei Hatano, Eiji Takimoto:
Rotation-Invariant Convolution Networks with Hexagon-Based Kernels. IEICE Trans. Inf. Syst. 107(2): 220-228 (2024) - [j32]Xuanke Jiang, Sherief Hashima, Kohei Hatano, Eiji Takimoto:
Online Job Scheduling with K Servers. IEICE Trans. Inf. Syst. 107(3): 286-293 (2024) - [j31]Ryotaro Mitsuboshi, Kohei Hatano, Eiji Takimoto:
Solving Linear Regression with Insensitive Loss by Boosting. IEICE Trans. Inf. Syst. 107(3): 294-300 (2024) - [c63]Xuanke Jiang, Sherief Hashima, Kohei Hatano, Eiji Takimoto:
Opportunistic Downlink User Connectivity in NOMA Enhanced NB-IoT Systems, A Semi-Matching Approach. WCNC 2024: 1-6 - 2023
- [j30]Ehab Mahmoud Mohamed
, Sherief Hashima
, Kohei Hatano
, Eiji Takimoto, Mohamed Abdel-Nasser
:
Load Balancing Multi-Player MAB Approaches for RIS-Aided mmWave User Association. IEEE Access 11: 15816-15830 (2023) - [c62]Yuta Kurokawa, Ryotaro Mitsuboshi, Haruki Hamasaki
, Kohei Hatano
, Eiji Takimoto
, Holakou Rahmanian:
Extended Formulations via Decision Diagrams. COCOON (2) 2023: 17-28 - [c61]Yiping Tang
, Kohei Hatano
, Eiji Takimoto
:
Boosting-Based Construction of BDDs for Linear Threshold Functions and Its Application to Verification of Neural Networks. DS 2023: 477-491 - [c60]Sherief Hashima, Zubair Md. Fadlullah, Mostafa M. Fouda, Kohei Hatano, Eiji Takimoto, Mohsen Guizani:
A Dual-Objective Bandit-Based Opportunistic Band Selection Strategy for Hybrid-Band V2X Metaverse Content Update. GLOBECOM 2023: 6880-6885 - [c59]Sherief Hashima, Mostafa M. Fouda, Kohei Hatano, Eiji Takimoto:
Advanced Learning Schemes for Metaverse Applications in B5G/6G Networks. MetaCom 2023: 799-804 - [c58]Sherief Hashima
, Ehab Mahmoud Mohamed, Kohei Hatano, Eiji Takimoto, Mostafa M. Fouda
, Zubair Md. Fadlullah:
On Enhancing WiGig Communications With A UAV-Mounted RIS System: A Contextual Multi-Armed Bandit Approach. PIMRC 2023: 1-7 - [i11]Yiping Tang, Kohei Hatano, Eiji Takimoto:
Boosting-based Construction of BDDs for Linear Threshold Functions and Its Application to Verification of Neural Networks. CoRR abs/2306.05211 (2023) - [i10]Yaxiong Liu, Atsuyoshi Nakamura, Kohei Hatano, Eiji Takimoto:
Pure exploration in multi-armed bandits with low rank structure using oblivious sampler. CoRR abs/2306.15856 (2023) - [i9]Ryotaro Mitsuboshi, Kohei Hatano, Eiji Takimoto:
An Improved Metarounding Algorithm via Frank-Wolfe. CoRR abs/2310.12629 (2023) - 2022
- [j29]Keigo Taga, Junjun Zheng
, Koichi Mouri, Shoichi Saito, Eiji Takimoto:
Firewall Traversal Method by Pseudo-TCP Encapsulation. IEICE Trans. Inf. Syst. 105-D(1): 105-115 (2022) - [j28]Hiroki Inayoshi
, Shohei Kakei
, Eiji Takimoto
, Koichi Mouri
, Shoichi Saito
:
Value-utilized taint propagation: toward precise detection of apps' information flows across Android API calls. Int. J. Inf. Sec. 21(5): 1127-1149 (2022) - [c57]Daiki Suehiro, Eiji Takimoto:
Simplified and unified analysis of various learning problems by reduction to Multiple-Instance Learning. UAI 2022: 1896-1906 - [i8]Ryotaro Mitsuboshi, Kohei Hatano, Eiji Takimoto:
Boosting as Frank-Wolfe. CoRR abs/2209.10831 (2022) - [i7]Yuta Kurokawa, Ryotaro Mitsuboshi, Haruki Hamasaki, Kohei Hatano, Eiji Takimoto, Holakou Rahmanian:
Extended Formulations via Decision Diagrams. CoRR abs/2211.06065 (2022) - 2021
- [c56]Hiroki Inayoshi
, Shohei Kakei, Eiji Takimoto, Koichi Mouri, Shoichi Saito
:
VTDroid: Value-based Tracking for Overcoming Anti-Taint-Analysis Techniques in Android Apps. ARES 2021: 29:1-29:6 - [c55]Yaxiong Liu, Xuanke Jiang, Kohei Hatano, Eiji Takimoto:
Expert advice problem with noisy low rank loss. ACML 2021: 1097-1112 - [c54]Yaxiong Liu, Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto:
An online semi-definite programming with a generalised log-determinant regularizer and its applications. ACML 2021: 1113-1128 - [c53]Sherief Hashima
, Ehab Mahmoud Mohamed, Kohei Hatano, Eiji Takimoto:
WiGig Wireless Sensor Selection Using Sophisticated Multi Armed Bandit Schemes. ICMU 2021: 1-6 - [c52]Yaxiong Liu
, Kohei Hatano
, Eiji Takimoto
:
Improved Algorithms for Online Load Balancing. SOFSEM 2021: 203-217 - [c51]Zhiyi Zhu, Toshikazu Nishimura, Eiji Takimoto, Junjun Zheng:
Performance Evaluation of Heterogeneous Cellular Networks Using Stochastic Petri Nets. SoftCOM 2021: 1-6 - 2020
- [j27]Sherief Hashima
, Kohei Hatano, Eiji Takimoto, Ehab Mahmoud Mohamed
:
Neighbor Discovery and Selection in Millimeter Wave D2D Networks Using Stochastic MAB. IEEE Commun. Lett. 24(8): 1840-1844 (2020) - [j26]Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai, Akiko Takeda:
Theory and Algorithms for Shapelet-Based Multiple-Instance Learning. Neural Comput. 32(8): 1580-1613 (2020) - [j25]Takahiro Fujita, Kohei Hatano, Eiji Takimoto:
Boosting over non-deterministic ZDDs. Theor. Comput. Sci. 806: 81-89 (2020) - [c50]Sherief Hashima
, Kohei Hatano, Eiji Takimoto, Ehab Mahmoud Mohamed:
Minimax Optimal Stochastic Strategy (MOSS) For Neighbor Discovery and Selection In Millimeter Wave D2D Networks. WPMC 2020: 1-6 - [i6]Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai, Akiko Takeda:
Theory and Algorithms for Shapelet-based Multiple-Instance Learning. CoRR abs/2006.01130 (2020) - [i5]Yaxiong Liu, Kohei Hatano, Eiji Takimoto:
Improved algorithms for online load balancing. CoRR abs/2007.07515 (2020) - [i4]Yaxiong Liu, Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto:
A generalised log-determinant regularizer for online semi-definite programming and its applications. CoRR abs/2012.05632 (2020)
2010 – 2019
- 2019
- [c49]Hiroki Inayoshi
, Shohei Kakei, Eiji Takimoto, Koichi Mouri, Shoichi Saito:
Prevention of Data Leakage due to Implicit Information Flows in Android Applications. AsiaJCIS 2019: 103-110 - [c48]Yiping Tang, Kohei Hatano, Eiji Takimoto:
Recognition of Japanese Historical Hand-Written Characters Based on Object Detection Methods. HIP@ICDAR 2019: 72-77 - [c47]Fumito Miyake
, Eiji Takimoto, Kohei Hatano
:
Succinct Representation of Linear Extensions via MDDs and Its Application to Scheduling Under Precedence Constraints. IWOCA 2019: 365-377 - 2018
- [j24]Daiki Suehiro, Kohei Hatano, Eiji Takimoto:
Efficient Reformulation of 1-Norm Ranking SVM. IEICE Trans. Inf. Syst. 101-D(3): 719-729 (2018) - [j23]Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto:
Online Linear Optimization with the Log-Determinant Regularizer. IEICE Trans. Inf. Syst. 101-D(6): 1511-1520 (2018) - [j22]Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto:
Tighter Generalization Bounds for Matrix Completion Via Factorization Into Constrained Matrices. IEICE Trans. Inf. Syst. 101-D(8): 1997-2004 (2018) - [j21]Takahiro Fujita, Kohei Hatano, Shuji Kijima
, Eiji Takimoto:
Online Combinatorial Optimization with Multiple Projections and Its Application to Scheduling Problem. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 101-A(9): 1334-1343 (2018) - [c46]Hiroki Ogawa, Eiji Takimoto, Koichi Mouri, Shoichi Saito:
User-Side Updating of Third-Party Libraries for Android Applications. CANDAR Workshops 2018: 452-458 - [c45]Takahiro Fujita, Kohei Hatano, Eiji Takimoto:
Boosting over Non-deterministic ZDDs. WALCOM 2018: 195-206 - [c44]Kosuke Matsumoto, Kohei Hatano, Eiji Takimoto:
Decision Diagrams for Solving a Job Scheduling Problem Under Precedence Constraints. SEA 2018: 5:1-5:12 - [i3]Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai, Akiko Takeda:
Multiple-Instance Learning by Boosting Infinitely Many Shapelet-based Classifiers. CoRR abs/1811.08084 (2018) - 2017
- [i2]Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai, Akiko Takeda:
Boosting the kernelized shapelets: Theory and algorithms for local features. CoRR abs/1709.01300 (2017) - [i1]Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto:
Online linear optimization with the log-determinant regularizer. CoRR abs/1710.10002 (2017) - 2016
- [j20]Nir Ailon, Kohei Hatano, Eiji Takimoto:
Bandit online optimization over the permutahedron. Theor. Comput. Sci. 650: 92-108 (2016) - [c43]Takumi Nakazono, Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto:
A Combinatorial Metrical Task System Problem Under the Uniform Metric. ALT 2016: 276-287 - 2015
- [c42]Takahiro Fujita, Kohei Hatano, Shuji Kijima
, Eiji Takimoto:
Online Linear Optimization for Job Scheduling Under Precedence Constraints. ALT 2015: 332-346 - [c41]Peter L. Bartlett, Wouter M. Koolen, Alan Malek, Eiji Takimoto, Manfred K. Warmuth:
Minimax Fixed-Design Linear Regression. COLT 2015: 226-239 - [c40]Issei Matsumoto, Kohei Hatano, Eiji Takimoto:
Online Density Estimation of Bradley-Terry Models. COLT 2015: 1343-1359 - [c39]Kei Uchizawa, Eiji Takimoto:
Lower Bounds for Linear Decision Trees with Bounded Weights. SOFSEM 2015: 412-422 - 2014
- [j19]Kazuki Teraoka, Kohei Hatano, Eiji Takimoto:
Efficient Sampling Method for Monte Carlo Tree Search Problem. IEICE Trans. Inf. Syst. 97-D(3): 392-398 (2014) - [c38]Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto, Koji Tsuda:
Online matrix prediction for sparse loss matrices. ACML 2014 - [c37]Nir Ailon, Kohei Hatano, Eiji Takimoto:
Bandit Online Optimization over the Permutahedron. ALT 2014: 215-229 - 2013
- [c36]Eiji Takimoto, Kohei Hatano:
Efficient Algorithms for Combinatorial Online Prediction. ALT 2013: 22-32 - [c35]Takahiro Fujita, Kohei Hatano, Eiji Takimoto:
Combinatorial Online Prediction via Metarounding. ALT 2013: 68-82 - 2012
- [c34]Daiki Suehiro, Kohei Hatano, Shuji Kijima
, Eiji Takimoto, Kiyohito Nagano:
Online Prediction under Submodular Constraints. ALT 2012: 260-274 - [c33]Shota Yasutake, Kohei Hatano, Eiji Takimoto, Masayuki Takeda:
Online Rank Aggregation. ACML 2012: 539-553 - 2011
- [j18]Shin-ichi Yoshida, Kohei Hatano, Eiji Takimoto, Masayuki Takeda:
Adaptive Online Prediction Using Weighted Windows. IEICE Trans. Inf. Syst. 94-D(10): 1917-1923 (2011) - [j17]Kei Uchizawa, Eiji Takimoto, Takao Nishizeki:
Size-energy tradeoffs for unate circuits computing symmetric Boolean functions. Theor. Comput. Sci. 412(8-10): 773-782 (2011) - [c32]Daiki Suehiro, Kohei Hatano, Eiji Takimoto:
Approximate Reduction from AUC Maximization to 1-Norm Soft Margin Optimization. ALT 2011: 324-337 - [c31]Shota Yasutake, Kohei Hatano, Shuji Kijima
, Eiji Takimoto, Masayuki Takeda:
Online Linear Optimization over Permutations. ISAAC 2011: 534-543 - [c30]Kei Uchizawa, Eiji Takimoto:
Lower Bounds for Linear Decision Trees via an Energy Complexity Argument. MFCS 2011: 568-579 - 2010
- [j16]Hideaki Fukuhara, Eiji Takimoto:
Lower Bounds on Quantum Query Complexity for Read-Once Formulas with XOR and MUX Operators. IEICE Trans. Inf. Syst. 93-D(2): 280-289 (2010) - [j15]Hideaki Fukuhara, Eiji Takimoto, Kazuyuki Amano:
NPN-Representatives of a Set of Optimal Boolean Formulas. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 93-A(6): 1008-1015 (2010) - [j14]Kei Uchizawa, Takao Nishizeki, Eiji Takimoto:
Energy and depth of threshold circuits. Theor. Comput. Sci. 411(44-46): 3938-3946 (2010)
2000 – 2009
- 2009
- [c29]Hideaki Fukuhara, Eiji Takimoto:
Lower Bounds on Quantum Query Complexity for Read-Once Decision Trees with Parity Nodes. CATS 2009: 89-98 - [c28]Kohei Hatano, Eiji Takimoto:
Linear Programming Boosting by Column and Row Generation. Discovery Science 2009: 401-408 - [c27]Kei Uchizawa, Takao Nishizeki, Eiji Takimoto:
Energy Complexity and Depth of Threshold Circuits. FCT 2009: 335-345 - [c26]Kei Uchizawa, Takao Nishizeki, Eiji Takimoto:
Size and Energy of Threshold Circuits Computing Mod Functions. MFCS 2009: 724-735 - 2008
- [j13]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) - [c25]Eiji Takimoto, Yoshihisa Kondo, Satoko Itaya, Ryutaro Suzuki, Sadao Obana:
Evaluation of Multi-Channel Flooding for Inter-Vehicle Communication. AINA Workshops 2008: 960-965 - [c24]Jun-ichi Moribe, Kohei Hatano, Eiji Takimoto, Masayuki Takeda:
Smooth Boosting for Margin-Based Ranking. ALT 2008: 227-239 - [c23]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 - 2007
- [c22]Marcus Hutter
, Rocco A. Servedio, Eiji Takimoto:
Editors' Introduction. ALT 2007: 1-8 - [c21]Kei Uchizawa, Eiji Takimoto:
An Exponential Lower Bound on the Size of Constant-Depth Threshold Circuits with Small Energy Complexity. CCC 2007: 169-178 - [e2]Marcus Hutter
, Rocco A. Servedio, Eiji Takimoto:
Algorithmic Learning Theory, 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings. Lecture Notes in Computer Science 4754, Springer 2007, ISBN 978-3-540-75224-0 [contents] - 2006
- [j12]Shigeaki Harada, Eiji Takimoto, Akira Maruoka:
Online Allocation with Risk Information. IEICE Trans. Inf. Syst. 89-D(8): 2340-2347 (2006) - [j11]Ricard Gavaldà
, Eiji Takimoto:
Foreword. Theor. Comput. Sci. 364(1): 1-2 (2006) - [c20]Shigeaki Harada, Eiji Takimoto, Akira Maruoka:
Aggregating Strategy for Online Auctions. COCOON 2006: 33-41 - 2005
- [c19]Shigeaki Harada, Eiji Takimoto, Akira Maruoka:
Online Allocation with Risk Information. ALT 2005: 343-355 - 2004
- [j10]Kenshi Matsuo, Tetsuya Koyama, Eiji Takimoto, Akira Maruoka:
Relationships between Horn Formulas and XOR-MDNF Formulas. IEICE Trans. Inf. Syst. 87-D(2): 343-351 (2004) - [c18]Eiji Takimoto, Syuhei Koya, Akira Maruoka:
Boosting Based on Divide and Merge. ALT 2004: 127-141 - 2003
- [j9]Eiji Takimoto, Manfred K. Warmuth:
Path Kernels and Multiplicative Updates. J. Mach. Learn. Res. 4: 773-818 (2003) - [j8]Eiji Takimoto, Akira Maruoka:
Top-down decision tree learning as information based boosting. Theor. Comput. Sci. 292(2): 447-464 (2003) - [e1]Ricard Gavaldà, Klaus P. Jantke, Eiji Takimoto:
Algorithmic Learning Theory, 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings. Lecture Notes in Computer Science 2842, Springer 2003, ISBN 3-540-20291-9 [contents] - 2002
- [j7]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) - [c17]Eiji Takimoto, Manfred K. Warmuth:
Path Kernels and Multiplicative Updates. COLT 2002: 74-89 - [c16]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 - [c15]Eiji Takimoto, Akira Maruoka:
Top-Down Decision Tree Boosting and Its Applications. Progress in Discovery Science 2002: 327-337 - 2001
- [j6]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
- [j5]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) - [c14]Eiji Takimoto, Manfred K. Warmuth:
The Last-Step Minimax Algorithm. ALT 2000: 279-290 - [c13]Eiji Takimoto, Manfred K. Warmuth:
The Minimax Strategy for Gaussian Density Estimation. pp. COLT 2000: 100-106 - [c12]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
1990 – 1999
- 1999
- [j4]Yoshifumi Sakai, Eiji Takimoto, Akira Maruoka:
Proper Learning Algorithm for Functions of k Terms under Smooth Distributions. Inf. Comput. 152(2): 188-204 (1999) - [c11]Eiji Takimoto, Manfred K. Warmuth:
Predicting Nearly as well as the best Pruning of a Planar Decision Graph. ALT 1999: 335-346 - 1998
- [c10]Akira Maruoka, Eiji Takimoto:
Structured Weight-Based Prediction Algorithms. ALT 1998: 127-142 - [c9]Eiji Takimoto, Akira Maruoka:
On the Boosting Algorithm for Multiclass Functions Based on Information-Theoretic Criterion for Approxiamtion. Discovery Science 1998: 256-267 - 1997
- [j3]Eiji Takimoto, Akira Miyashiro, Akira Maruoka, Yoshifumi Sakai:
Learning Orthogonal F-Horn Formulas. Theor. Comput. Sci. 185(1): 177-190 (1997) - [c8]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 - 1996
- [c7]Eiji Takimoto, Yoshifumi Sakai, Akira Maruoka:
Learnability of Exclusive-Or Expansion Based on Monotone DNF Formulas. ALT 1996: 12-25 - 1995
- [j2]Eiji Takimoto, Akira Maruoka:
On the Sample Complexity of Consistent Learning with One-Sided Error. IEICE Trans. Inf. Syst. 78-D(5): 518-525 (1995) - [c6]Akira Miyashiro, Eiji Takimoto, Yoshifumi Sakai, Akira Maruoka:
Learning Orthogonal F-Horn Formulas. ALT 1995: 110-122 - [c5]Yoshifumi Sakai, Eiji Takimoto, Akira Maruoka:
Proper Learning Algorithm for Functions of k Terms Under Smooth Distributions. COLT 1995: 206-213 - 1994
- [c4]Eiji Takimoto, Ichiro Tajika, Akira Maruoka:
Mutual Information Gaining Algorithm and Its Relation to PAC-Learning Algorithm. AII/ALT 1994: 547-559 - 1993
- [j1]Eiji Takimoto, Akira Maruoka:
Relationships between learning and information compression based on PAC learning model. Syst. Comput. Jpn. 24(8): 47-58 (1993) - [c3]Eiji Takimoto, Akira Maruoka:
On the Sample Complexity of Consistent Learning with One-Sided Error. ALT 1993: 265-278 - [c2]Eiji Takimoto, Akira Maruoka:
Conservativeness and Monotonicity for Learning Algorithms. COLT 1993: 377-383 - 1991
- [c1]Eiji Takimoto, Akira Maruoka:
Relationships between PAC-learning algorithms and weak Occam algorithms. ALT 1991: 151-162
Coauthor Index
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