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ORCIDHideo Hirose
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2020 – today
- 2023
[j14]Hideo Hirose
:
An Insight to Estimated Item Response Matrix in Item Response Theory. IEEE Access 11: 82239-82247 (2023)- 2022
- [i2]Hideo Hirose:
Matrix Decomposition Perspective for Accuracy Assessment of Item Response Theory. CoRR abs/2203.03112 (2022) - 2020
- [c26]Hideo Hirose:
Current Failure Prediction for Final Examination using Past Trends of Weekly Online Testing. IIAI-AAI 2020: 142-148 - [c25]Hideo Hirose:
More Accurate Evaluation of Student's Ability Based on A Newly Proposed Ability Equation. IIAI-AAI 2020: 176-182
2010 – 2019
- 2019
- [i1]Hideo Hirose:
Prediction of Success or Failure for Final Examination using Nearest Neighbor Method to the Trend of Weekly Online Testing. CoRR abs/1901.02056 (2019) - 2018
- [c24]Hideo Hirose:
Success/Failure Prediction for Final Examination Using the Trend of Weekly Online Testing. IIAI-AAI 2018: 139-145 - [c23]Hideo Hirose:
Attendance to Lectures is Crucial in Order not to Drop Out. IIAI-AAI 2018: 194-198 - [c22]Hideo Hirose:
Time Duration Statistics Spent for Tackling Online Testing. IIAI-AAI 2018: 221-225 - 2017
- [c21]Hideo Hirose, Masanori Takatou, Yusuke Yamauchi, Fujio Kubo, Tetsuji Taniguchi, Mitsunori Imaoka, Tetsuya Koyama:
Rediscovery of Initial Habituation Importance Learned from Analytics of Learning Check Testing in Mathematics for Undergraduate Students. IIAI-AAI 2017: 482-486 - 2016
- [c20]Hideo Hirose:
Meticulous Learning Follow-Up Systems for Undergraduate Students Using the Online Item Response Theory. IIAI-AAI 2016: 427-432 - [c19]Hideo Hirose, Masanori Takatou, Yusuke Yamauchi, Tetsuji Taniguchi, Tatsuhiro Honda, Fujio Kubo, Mitsunori Imaoka, Tetsuya Koyama:
Questions and Answers Database Construction for Adaptive Online IRT Testing Systems: Analysis Course and Linear Algebra Course. IIAI-AAI 2016: 433-438 - [c18]Hideo Hirose:
Learning Analytics to Adaptive Online IRT Testing Systems "Ai Arutte" Harmonized with University Textbooks. IIAI-AAI 2016: 439-444 - [c17]Yoshiko Tokusada, Hideo Hirose:
Evaluation of Abilities by Grouping for Small IRT Testing Systems. IIAI-AAI 2016: 445-449 - [c16]Takenori Sakumura, Hideo Hirose:
Bias Reduction of Abilities for Adaptive Online IRT Testing Systems. IIAI-AAI 2016: 450-455 - 2015
- [j13]Hideo Hirose, Masakazu Tokunaga, Takenori Sakumura, Junaida Binti Sulaiman, Herdianti Darwis:
Matrix Approach for the Seasonal Infectious Disease Spread Prediction. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 98-A(10): 2010-2017 (2015) - [c15]Naoki Tabuchi, Shinya Nakano, Hideo Hirose:
Optimum Life Test Plan under the Thermal Stress Deterioration Using the Mechanical Strength. ACIT-CSI 2015: 268-273 - 2014
- [j12]Junaida Binti Sulaiman, Herdianti Darwis, Hideo Hirose:
Monthly Maximum Accumulated Precipitation Forecasting Using Local Precipitation Data and Global Climate Modes. J. Adv. Comput. Intell. Intell. Informatics 18(6): 999-1006 (2014) - [c14]Yu Aizawa, Hideo Hirose:
Bias Correction for the Trade-Off Curve in the Tree-Ga Bump Hunting. IIAI-AAI 2014: 126-130 - 2013
- [j11]Faisal Zaman, Hideo Hirose:
DF-SVM: a decision forest constructed on artificially enlarged feature space by support vector machine. Artif. Intell. Rev. 40(4): 467-494 (2013) - 2012
- [j10]Sirajum Monira Sumi, Faisal Zaman, Hideo Hirose:
A rainfall forecasting method using machine learning models and its application to the Fukuoka city case. Int. J. Appl. Math. Comput. Sci. 22(4): 841-854 (2012) - [j9]Hideo Hirose:
Estimation of the number of failures in the Weibull model using the ordinary differential equation. Eur. J. Oper. Res. 223(3): 722-731 (2012) - [c13]Faisal Zaman, Sirajum Monira Sumi, Hideo Hirose:
DRFLogitBoost: A Double Randomized Decision Forest Incorporated with LogitBoosted Decision Stumps. ACIIDS (1) 2012: 291-300 - [c12]Hideo Hirose, Yusuke Soejima, Kei Hirose:
NNRMLR: A Combined Method of Nearest Neighbor Regression and Multiple Linear Regression. IIAI-AAI 2012: 351-356 - [c11]Hideo Hirose, Liangliang Wang:
Prediction of Infectious Disease Spread Using Twitter: A Case of Influenza. PAAP 2012: 100-105 - 2011
- [j8]Faisal Zaman, Hideo Hirose:
Classification Performance of Bagging and Boosting Type Ensemble Methods with Small Training Sets. New Gener. Comput. 29(3): 277-292 (2011) - [c10]Sirajum Monira Sumi, Faisal Zaman, Hideo Hirose:
A Novel Hybrid Forecast Model with Weighted Forecast Combination with Application to Daily Rainfall Forecast of Fukuoka City. ACIIDS (2) 2011: 262-271 - [c9]Faisal Zaman, Hideo Hirose:
Estimation of Optimal Sample Size of Decision Forest with SVM Using Embedded Cross-Validation Method. ACIIDS (2) 2011: 272-281 - [c8]Sirajum Monira Sumi, Faisal Zaman, Hideo Hirose:
A Neural Network Ensemble Incorporated with Dynamic Variable Selection for Rainfall Forecast. SNPD 2011: 7-12 - 2010
- [c7]Faisal Zaman, Hideo Hirose:
A Comparative Study on the Performance of Several Ensemble Methods with Low Subsampling Ratio. ACIIDS (2) 2010: 320-329 - [c6]Faisal Zaman, Mohammad Mesbah Uddin, Hideo Hirose:
On Selecting Additional Predictive Models in Double Bagging Type Ensemble Method. ICCSA (4) 2010: 199-208 - [c5]Hideo Hirose:
Assessment of the Trade-off Curve Accuracy in the Bump Hunting Using the Tree-GA. WKDD 2010: 597-600
2000 – 2009
- 2009
- [j7]Faisal Zaman, Hideo Hirose:
Double SVMBagging: A New Double Bagging with Support Vector Machine. Eng. Lett. 17(2): 128-140 (2009) - [j6]Kotaro Tsuru, Hideo Hirose:
Estimation for the Weibull Power Law Parameters in the Step-up Voltage Test. Eng. Lett. 17(2): 141-145 (2009) - [j5]Yuki Toyosaka, Hideo Hirose:
The Consistency of the Pandemic Simulations between the SEIR Model and the MAS Model. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 92-A(7): 1558-1562 (2009) - [c4]Faisal Zaman, Hideo Hirose:
An Experimental Study on a New Ensemble Method using Robust and Order Statistics. DMIN 2009: 333-339 - [c3]Yuki Toyosaka, Hideo Hirose:
Pandemic Simulations by MADE: A Combination of Multi-agent and Differential Euations. PDPTA 2009: 331-335 - [c2]Faisal Zaman, Hideo Hirose:
Effect of Subsampling Rate on Subbagging and Related Ensembles of Stable Classifiers. PReMI 2009: 44-49 - 2007
- [j4]Hideo Hirose:
More accurate breakdown voltage estimation for the new step-up test method in the gumbel distribution model. Eur. J. Oper. Res. 177(1): 406-419 (2007) - [j3]Hideo Hirose:
The mixed trunsored model with applications to SARS. Math. Comput. Simul. 74(6): 443-453 (2007) - [c1]Hideo Hirose, Takahiro Yukizane, T. Deguchi:
The Bump Hunting Method and Its Accuracy Using the Genetic Algorithm with Application to Real Customer Data. CIT 2007: 128-132 - 2006
- [j2]Takahiro Yukizane, Shin-ya Ohi, Eiji Miyano, Hideo Hirose:
The Bump Hunting Method Using the Genetic Algorithm with the Extreme-Value Statistics. IEICE Trans. Inf. Syst. 89-D(8): 2332-2339 (2006) - 2003
- [j1]Hideo Hirose, Yoshio Komori:
Maximum Likelihood Estimation in a Mixture Regression Model Using the Continuation Method. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 86-A(5): 1256-1265 (2003)
Coauthor Index
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