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2020 – today
- 2024
[j69]Iko Nakari
, Keiki Takadama:
Explainable Non-Contact Sleep Apnea Syndrome Detection Based on Comparison of Random Forests. IEEE Access 12: 12001-12009 (2024)- [j68]Kazuteru Miyazaki, Keiki Takadama:
Editorial: Cutting Edge of Reinforcement Learning and its Hybrid Methods. J. Adv. Comput. Intell. Intell. Informatics 28(2): 379 (2024) - [j67]Fumito Uwano, Satoshi Hasegawa, Keiki Takadama:
Inverse Reinforcement Learning with Agents' Biased Exploration Based on Sub-Optimal Sequential Action Data. J. Adv. Comput. Intell. Intell. Informatics 28(2): 380-392 (2024) - [j66]Iko Nakari, Keiki Takadama:
Non-Contact Sleep Stage Estimation by Updating its Prediction Probabilities According to Ultradian Rhythm. J. Adv. Comput. Intell. Intell. Informatics 28(2): 444-453 (2024) - [c213]Takashi Kido, Keiki Takadama:
The Challenges for GenAI in Social and Individual Well-Being. AAAI Spring Symposia 2024: 365-367 - [c212]Iko Nakari, Keiki Takadama:
Sleep Stage Estimation by Introduction of Sleep Domain Knowledge to AI: Towards Personalized Sleep Counseling System with GenAI. AAAI Spring Symposia 2024: 368-373 - [c211]Daiki Shintani, Iko Nakari, Satomi Washizaki, Keiki Takadama:
NREM3 Sleep Stage Estimation Based on Accelerometer by Body Movement Count and Biological Rhythms. AAAI Spring Symposia 2024: 405-411 - [c210]Keiki Takadama:
What Is a Correct Output by Generative AI From the Viewpoint of Well-Being? - Perspective From Sleep Stage Estimation -. AAAI Spring Symposia 2024: 434-439 - [c209]Ryuki Ishizawa, Hiroyuki Sato, Keiki Takadama:
From Multipoint Search to Multiarea Search: Novelty-Based Multi-Objectivization for Unbounded Search Space Optimization. CEC 2024: 1-8 - [c208]Shio Kawakami, Keiki Takadama, Hiroyuki Sato:
Evolutionary Constrained Multi-Factorial Optimization Based on Task Similarity. CEC 2024: 1-8 - [c207]Keigo Mochizuki, Tomoki Ishizuka, Naoya Yatsu, Hiroyuki Sato, Keiki Takadama:
Design of Generalized and Specialized Helper Objectives for Multi-objective Continuous Optimization Problems. CEC 2024: 1-8 - [c206]Naru Okumura, Keiki Takadama, Hiroyuki Sato:
Pareto Front Estimation Model Optimization for Aggregative Solution Set Representation. CEC 2024: 1-8 - [c205]Kazuma Sato, Naru Okumura, Keiki Takadama, Hiroyuki Sato:
Should Multi-objective Evolutionary Algorithms Use Always Best Non-dominated Solutions as Parents? CEC 2024: 1-8 - [c204]Ryo Takamiya, Minami Miyakawa, Keiki Takadama, Hiroyuki Sato:
Push and Pull Search with Directed Mating for Constrained Multi-objective Optimization. CEC 2024: 1-8 - [c203]Shoichiro Tanaka, Arnaud Liefooghe, Keiki Takadama, Hiroyuki Sato:
Designing Helper Objectives in Multi-Objectivization. CEC 2024: 1-8 - [c202]Naoya Yatsu, Hiroki Shiraishi, Hiroyuki Sato, Keiki Takadama:
Prototype Generation with the sUpervised Classifier System on kNN Matching. CEC 2024: 1-8 - [c201]Shoichiro Tanaka, Gabriela Ochoa, Arnaud Liefooghe, Keiki Takadama, Hiroyuki Sato:
Approximating Pareto Local Optimal Solution Networks. GECCO 2024 - [c200]Naoya Yatsu, Hiroki Shiraishi, Hiroyuki Sato, Keiki Takadama:
Generating High-Dimensional Prototypes with a Classifier System by Evolving in Latent Space. GECCO Companion 2024: 2127-2130 - [c199]Shunsuke Ueki, Keiki Takadama:
Multi-Agent Archive-Based Inverse Reinforcement Learning by Improving Suboptimal Experts. ICAART (3) 2024: 1362-1369 - 2023
- [j65]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Directional Pareto Front and Its Estimation to Encourage Multi-Objective Decision-Making. IEEE Access 11: 20619-20634 (2023) - [j64]Takashi Kido, Keiki Takadama:
AAAI 23 Spring Symposium Report on "Socially Responsible AI for Well-Bing". AI Mag. 44(2): 211-212 (2023) - [j63]Kazushi Fujino, Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Adaptive action-prediction cortical learning algorithm under uncertain environments. Int. J. Hybrid Intell. Syst. 19(3): 225-245 (2023) - [c198]Takashi Kido, Keiki Takadama:
The Challenges for Socially Responsible AI for Well-being. AAAI Spring Symposium: SRAI 2023: 1-3 - [c197]Keiki Takadama:
How to Handle Wellbeing in Socially Responsible AI? - Findings from Sleep Perspective -. AAAI Spring Symposium: SRAI 2023: 4-8 - [c196]Iko Nakari, Keiki Takadama:
Sleep Stage Estimation based on The Estimated Probability of each Sleep Stage by Learning with Specialized Models. AAAI Spring Symposium: SRAI 2023: 103-110 - [c195]Miki Nakai, Tomoyoshi Ashikaga, Junichi Shimizu, Keiki Takadama:
Thermal environment evaluation considering nap start time. AAAI Spring Symposium: SRAI 2023: 121-127 - [c194]Ryuki Ishizawa, Tomoya Kuga, Yusuke Maekawa, Hiroyuki Sato, Keiki Takadama:
Toward Unbounded Search Space Exploration by Particle Swarm Optimization in Multi-Modal Optimization Problem. CEC 2023: 1-8 - [c193]Naoya Matsuda, Iko Nakari, Keiki Takadama, Kohta Katayama, Makoto Shiraishi, Yoshiyuki Ohira:
Alzheimer Dementia Detection Based on Time-series Instability of Heart Rate. EMBC 2023: 1-4 - [c192]Iko Nakari, Keiki Takadama:
Personalized Non-contact Sleep Stage Estimation with Weighted Probability Estimation by Ultradian Rhythm. EMBC 2023: 1-4 - [c191]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling. EMO 2023: 218-230 - [c190]Shoichiro Tanaka, Keiki Takadama, Hiroyuki Sato:
Multi-objectivization Relaxes Multi-funnel Structures in Single-objective NK-landscapes. EvoCOP 2023: 195-210 - [c189]Fumito Uwano, Keiki Takadama:
Reinforcement Learning in Cyclic Environmental Changes for Agents in Non-Communicative Environments: A Theoretical Approach. EXTRAAMAS 2023: 143-159 - [c188]Naoya Yatsu, Hiroki Shiraishi, Hiroyuki Sato, Keiki Takadama:
Exploring High-dimensional Rules Indirectly via Latent Space Through a Dimensionality Reduction for XCS. GECCO 2023: 606-614 - [c187]Iko Nakari, Masahiro Nakashima, Keiki Takadama:
Personalized Sleep Stage Estimation Based on Time Series Probability of Estimation for Each Label with Wearable 3-Axis Accelerometer. HCI (5) 2023: 531-542 - [e10]Takashi Kido, Keiki Takadama:
Post-event Proceedings of the AAAI Spring Symposium: Socially Responsible AI for Well-being (AAAI-SRAI 2023) co-located with Association for the Advancement of Artificial Intelligence 2023 Spring Symposium (AAAI-Spring Symposium 2023), Hyatt Regency San Francisco Airport (Hybrid), March 27-29, 2023. CEUR Workshop Proceedings 3527, CEUR-WS.org 2023 [contents] - 2022
- [c186]Takashi Kido, Keiki Takadama:
The Challenges for Fairness and Well-being. AAAI Spring Symposium: HFIF 2022: 1-3 - [c185]Keiki Takadama:
How to Cope with Bias in Well-being AI? AAAI Spring Symposium: HFIF 2022: 4-7 - [c184]Iko Nakari, Naoya Matsuda, Keiki Takadama:
REM Estimation Based on Combination of Multi-Timescale Estimations and Automatic Adjustment of Personal Bio-vibration Data of Mattress Sensor. AAAI Spring Symposium: HFIF 2022: 74-80 - [c183]Naoya Matsuda, Taiki Senju, Iko Nakari, Keiki Takadama:
Analysis of Circadian Rhythm Estimation Process for Improving the Accuracy of Alzheimer Dementia Detection. AAAI Spring Symposium: HFIF 2022: 81-87 - [c182]Miki Nakai, Tomoyoshi Ashikaga, Takahiro Ohga, Keiki Takadama:
A Thermal Environment that Promotes Efficient Napping. AAAI Spring Symposium: HFIF 2022: 88-93 - [c181]Hiroki Shiraishi, Yohei Havamizu, Hiroyuki Sato, Keiki Takadama:
Beta Distribution based XCS Classifier System. CEC 2022: 1-8 - [c180]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Supervised Multi-Objective Optimization Algorithm Using Estimation. CEC 2022: 1-8 - [c179]Shoichiro Tanaka, Keiki Takadama, Hiroyuki Sato:
Impacts of Single-objective Landscapes on Multi-objective Optimization. CEC 2022: 1-8 - [c178]Naoya Yatsu, Hiroki Shiraishi, Hiroyuki Sato, Keiki Takadama:
XCSR with VAE using Gaussian Distribution Matching: From Point to Area Matching in Latent Space for Less-overlapped Rule Generation in Observation Space. CEC 2022: 1-8 - [c177]Iko Nakari, Naoya Matsuda, Keiki Takadama:
Non-Contact REM Sleep Estimation Correction by Time-Series Confidence of Predictions: From Binary to Continuous Prediction in Machine Learning for Biological Data. EMBC 2022: 1008-1011 - [c176]Naoya Matsuda, Iko Nakari, Keiki Takadama:
Unstable Circadian Rhythm of Heart Rate of Alzheimer Dementia Based on Biological Data of Mattress Sensor. EMBC 2022: 1129-1132 - [c175]Hiroki Shiraishi, Yohei Hayamizu, Iko Nakari, Hiroyuki Sato, Keiki Takadama:
Inheritance vs. Expansion: Generalization Degree of Nearest Neighbor Rule in Continuous Space as Covering Operator of XCS. EvoApplications 2022: 352-368 - [c174]Hiroki Shiraishi, Yohei Hayamizu, Hiroyuki Sato, Keiki Takadama:
Absumption based on overgenerality and condition-clustering based specialization for XCS with continuous-valued inputs. GECCO 2022: 422-430 - [c173]Hiroki Shiraishi, Yohei Hayamizu, Hiroyuki Sato, Keiki Takadama:
Can the same rule representation change its matching area?: enhancing representation in XCS for continuous space by probability distribution in multiple dimension. GECCO 2022: 431-439 - [c172]Fumito Uwano, Daiki Yamane, Keiki Takadama:
Design of Human-Agent-Group Interaction for Correct Opinion Sharing on Social Media. HCI (4) 2022: 146-165 - [c171]Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Synergistic Effect of Adaptive Synapse Arrangement and Column-based Decoder in Cortical Learning Algorithm. SCIS/ISIS 2022: 1-6 - [c170]Kazushi Fujino, Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Adaptive Synapse Adjustment for Multivariate Cortical Learning Algorithm. SCIS/ISIS 2022: 1-8 - [e9]Takashi Kido, Keiki Takadama:
Proceedings of the Symposium How Fair is Fair? Achieving Wellbeing AI co-located with Association for the Advancement of Artificial Intelligence 2022 Spring Symposium (AAAI-Spring Symposium 2022), Stanford, CA, March 21-23, 2022. CEUR Workshop Proceedings 3276, CEUR-WS.org 2022 [contents] - 2021
- [j62]Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Adaptive Synapse Arrangement in Cortical Learning Algorithm. J. Adv. Comput. Intell. Intell. Informatics 25(4): 450-466 (2021) - [c169]Yohei Hayamizu, Saeid Amiri, Kishan Chandan, Keiki Takadama, Shiqi Zhang:
Guiding Robot Exploration in Reinforcement Learning via Automated Planning. ICAPS 2021: 625-633 - [c168]Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Double-Layered Cortical Learning Algorithm for Time-Series Prediction. BICT 2021: 33-44 - [c167]Shio Kawakami, Keiki Takadama, Hiroyuki Sato:
Multi-factorial Evolutionary Algorithm Using Objective Similarity Based Parent Selection. BICT 2021: 45-60 - [c166]Masakazu Tadokoro, Hiroyuki Sato, Keiki Takadama:
XCS with Weight-based Matching in VAE Latent Space and Additional Learning of High-Dimensional Data. CEC 2021: 304-310 - [c165]Hiroki Shiraishi, Masakazu Tadokoro, Yohei Hayamizu, Yukiko Fukumoto, Hiroyuki Sato, Keiki Takadama:
Increasing Accuracy and Interpretability of High-Dimensional Rules for Learning Classifier System. CEC 2021: 311-318 - [c164]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Weight Vector Arrangement Using Virtual Objective Vectors in Decomposition-based MOEA. CEC 2021: 1462-1469 - [c163]Iko Nakari, Keiki Takadama:
Sleep Apnea Syndrome Detection Based on Degree of Convexity of Logarithmic Spectrum Calculated from Overnight Bio-vibration Data of Mattress Sensor. EMBC 2021: 2270-2273 - [c162]Naoya Matsuda, Iko Nakari, Keiki Takadama:
Alzheimer Dementia Detection Based on Unstable Circadian Rhythm Waves Extracted from Heartrate. EMBC 2021: 4473-4476 - [c161]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Pareto Front Estimation Using Unit Hyperplane. EMO 2021: 126-138 - [c160]Sho Kajihara, Hiroyuki Sato, Keiki Takadama:
Generating Duplex Routes for Robust Bus Transport Network by Improved Multi-objective Evolutionary Algorithm Based on Decomposition. EvoApplications 2021: 65-80 - [c159]Hiroki Shiraishi, Masakazu Tadokoro, Yohei Hayamizu, Yukiko Fukumoto, Hiroyuki Sato, Keiki Takadama:
Misclassification detection based on conditional VAE for rule evolution in learning classifier system. GECCO Companion 2021: 169-170 - [c158]Yoshimiki Maekawa, Tomohiro Yamaguchi, Keiki Takadama:
Analyzing Early Stage of Forming a Consensus from Viewpoint of Majority/Minority Decision in Online-Barnga. HCI (5) 2021: 269-285 - [c157]Naoya Matsuda, Iko Nakari, Ryotaro Arai, Hiroyuki Sato, Keiki Takadama, Masanori Hirose, Hiroshi Hasegawa, Makoto Shiraishi, Takahide Matsuda:
Alzheimer Dementia Detection based on Circadian Rhythm Disorder of Heartrate. LifeTech 2021: 360-364 - [i2]Fumito Uwano, Keiki Takadama:
Directionality Reinforcement Learning to Operate Multi-Agent System without Communication. CoRR abs/2110.05773 (2021) - 2020
- [j61]Sotetsu Suzugamine, Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Self-Structured Cortical Learning Algorithm by Dynamically Adjusting Columns and Cells. J. Adv. Comput. Intell. Intell. Informatics 24(2): 185-198 (2020) - [j60]Fumito Uwano, Keiki Takadama:
Reward Value-Based Goal Selection for Agents' Cooperative Route Learning Without Communication in Reward and Goal Dynamism. SN Comput. Sci. 1(3): 182 (2020) - [j59]Tomohiro Harada, Keiki Takadama:
Analysis of semi-asynchronous multi-objective evolutionary algorithm with different asynchronies. Soft Comput. 24(4): 2917-2939 (2020) - [c156]Masakazu Tadokoro, Satoshi Hasegawa, Takato Tatsumi, Hiroyuki Sato, Keiki Takadama:
Local Covering: Adaptive Rule Generation Method Using Existing Rules for XCS. CEC 2020: 1-8 - [c155]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Non-dominated Solution Sampling Using Environmental Selection in EMO algorithms. CEC 2020: 1-9 - [c154]Kensuke Kano, Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Preliminary study of adaptive grid-based decomposition on many-objective evolutionary optimization. GECCO Companion 2020: 1373-1380 - [c153]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Incremental lattice design of weight vector set. GECCO Companion 2020: 1486-1494 - [c152]Kohei Yamamoto, Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Visual mapping of multi-objective optimization problems and evolutionary algorithms. GECCO Companion 2020: 1872-1879 - [c151]Yoshimiki Maekawa, Fumito Uwano, Eiki Kitajima, Keiki Takadama:
How to Emote for Consensus Building in Virtual Communication. HCI (5) 2020: 194-205 - [c150]Shio Kawakami, Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Distance Minimization Problems for Multi-factorial Evolutionary Optimization Benchmarking. HIS 2020: 710-719 - [c149]Iko Nakari, Eiki Kitajima, Yusuke Tajima, Keiki Takadama:
Non-contact Sleep Apnea Syndrome Detection Based on What Random Forests Learned. LifeTech 2020: 240-244 - [c148]Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Column-based Decoder of Internal Prediction Representation in Cortical Learning Algorithms. SCIS/ISIS 2020: 1-7 - [c147]Yukiko Fukumoto, Masakazu Tadokoro, Keiki Takadama:
Cooperative Multi-agent Inverse Reinforcement Learning Based on Selfish Expert and its Behavior Archives. SSCI 2020: 2202-2209 - [i1]Yohei Hayamizu, Saeid Amiri, Kishan Chandan, Shiqi Zhang, Keiki Takadama:
Guided Dyna-Q for Mobile Robot Exploration and Navigation. CoRR abs/2004.11456 (2020)
2010 – 2019
- 2019
- [j58]Ioana Baldini, Clark W. Barrett, Antonio Chella, Carlos Cinelli, David Gamez, Leilani H. Gilpin, Knut Hinkelmann, Dylan Holmes, Takashi Kido, Murat Kocaoglu, William F. Lawless, Alessio Lomuscio, Jamie C. Macbeth, Andreas Martin, Ranjeev Mittu, Evan Patterson, Donald Sofge, Prasad Tadepalli, Keiki Takadama, Shomir Wilson:
Reports of the AAAI 2019 Spring Symposium Series. AI Mag. 40(3): 59-66 (2019) - [c146]Takashi Kido, Keiki Takadama:
The Challenges for Interpretable AI for Well-being. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c145]Iko Nakari, Yusuke Tajima, Akari Tobaru, Keiki Takadama:
WAKE Detection During Sleep using Random Forest for Apnea Syndrome Patients. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c144]Keiki Takadama:
What Makes It Difficult To Apply AI Into Well-being and Its Solution: An Example of Sleep Apnea Syndrome. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c143]Ryo Takano, Sho Kajihara, Satoshi Hasegawa, Eiki Kitajima, Keiki Takadama, Toru Shimuta, Toru Yabe, Hideo Matsumoto:
Toward Good Circadian Rhythm through an valuate of Stress Condition. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c142]Ryo Takano, Akari Tobaru, Iko Nakari, Keiki Takadama:
Sleep Stage Estimation Through Mattress Sensor. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c141]Akari Tobaru, Yusuke Tajima, Keiki Takadama:
Sleep Stage Estimation using Heart Rate Variability divided by Sleep Cycle with Relative Evaluation. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c140]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
A Distribution Control of Weight Vector Set for Multi-objective Evolutionary Algorithms. BICT 2019: 70-80 - [c139]Takuya Iwase, Ryo Takano, Fumito Uwano, Hiroyuki Sato, Keiki Takadama:
Niche Radius Adaptation in Bat Algorithm for Locating Multiple Optima in Multimodal Functions. CEC 2019: 800-807 - [c138]Keiki Takadama, Daichi Yamazaki, Masaya Nakata, Hiroyuki Sato:
Complex-Valued-based Learning Classifier System for POMDP Environments. CEC 2019: 1852-1859 - [c137]Takato Tatsumi, Keiki Takadama:
Comparison of Statistical Table- and Non-Statistical Table-based XCS in Noisy Environments. CEC 2019: 1875-1882 - [c136]Masakazu Tadokoro, Satoshi Hasegawa, Takato Tatsumi, Hiroyuki Sato, Keiki Takadama:
Knowledge Extraction from XCSR Based on Dimensionality Reduction and Deep Generative Models. CEC 2019: 1883-1890 - [c135]Keiki Takadama, Keiji Sato, Hiroyuki Sato:
Evolving Generalized Solutions for Robust Multi-objective Optimization: Transportation Analysis in Disaster. EMO 2019: 491-503 - [c134]Takato Tatsumi, Keiki Takadama:
XCS-CR for handling input, output, and reward noise. GECCO (Companion) 2019: 1303-1311 - [c133]Tomohiro Yamaguchi, Shota Nagahama, Yoshihiro Ichikawa, Keiki Takadama:
Model-Based Multi-objective Reinforcement Learning with Unknown Weights. HCI (5) 2019: 311-321 - [c132]Yoshimiki Maekawa, Fumito Uwano, Eiki Kitajima, Keiki Takadama:
How to Design Adaptable Agents to Obtain a Consensus with Omoiyari. HCI (4) 2019: 462-475 - [c131]Ryota Kobayashi, Ryo Takano, Hiroyuki Sato, Keiki Takadama:
Simultaneous Local Adaptation for Different Local Properties. IES 2019: 216-227 - [c130]Takahiro Majima, Keiki Takadama, Daisuke Watanabe, Taro Aratani, Keiji Sato:
Application of Multi Agent System and Transition Matrix Analysis to Logistics System for Equal Distribution under Disaster Situation. SICE 2019: 108-114 - [c129]Iko Nakari, Akinori Murata, Eiki Kitajima, Hiroyuki Sato, Keiki Takadama:
Sleep Apnea Syndrome Detection based on Biological Vibration Data from Mattress Sensor. SSCI 2019: 550-556 - [e8]Takashi Kido, Keiki Takadama:
Proceedings of the Symposium Interpretable AI for Well-being: Understanding Cognitive Bias and Social Embeddedness co-located with Association for the Advancement of Artificial Intelligence 2019 Spring Symposium (AAAI-Spring Symposium 2019), Stanford, CA, March 25-27, 2019. CEUR Workshop Proceedings 2448, CEUR-WS.org 2019 [contents] - 2018
- [j57]Christopher Amato, Haitham Bou-Ammar, Elizabeth F. Churchill, Erez Karpas, Takashi Kido, Mike Kuniavsky, William F. Lawless, Francesca Rossi, Frans A. Oliehoek, Stephen Russell, Keiki Takadama, Siddharth Srivastava, Karl Tuyls, Philip van Allen, Kristen Brent Venable, Peter Vrancx, Shiqi Zhang:
Reports on the 2018 AAAI Spring Symposium Series. AI Mag. 39(4): 29-35 (2018) - [j56]Takahiro Majima, Keiki Takadama, Daisuke Watanabe, Taro Aratani, Keiji Sato:
Transportation simulator for disaster circumstance and bottleneck analysis. Artif. Life Robotics 23(4): 593-599 (2018) - [c128]Takashi Kido, Keiki Takadama:
The Challenges for Understanding Cognitive Bias and Humanity for Well-Being AI - Beyond Machine Intelligence. AAAI Spring Symposia 2018 - [c127]Yusuke Tajima, Akinori Murata, Tomohiro Harada, Keiki Takadama:
Sleep Stage Re-Estimation Method According To Sleep Cycle Change. AAAI Spring Symposia 2018 - [c126]Keiki Takadama:
Can Machine Learning Correct Commonly Accepted Knowledge and Provide Understandable Knowledge in Care Support Domain? Tackling Cognitive Bias and Humanity from Machine Learning Perspective. AAAI Spring Symposia 2018 - [c125]Ryo Takano, Satoshi Hasegawa, Yuta Umenai, Takato Tatsumi, Keiki Takadama, Toru Shimuta, Toru Yabe, Hideo Matsumoto:
Study of Analytical Methods on the Relationship between Sleep Quality and Stress with a focus on Human Circadian Rhythm. AAAI Spring Symposia 2018 - [c124]Akari Tobaru, Fumito Uwano, Takuya Iwase, Kazuma Matsumoto, Ryo Takano, Yusuke Tajima, Yuta Umenai, Keiki Takadama:
Improving Sleep Stage Estimation Accuracy by Circadian Rhythm Extracted from a Low Frequency Component of Heart Rate. AAAI Spring Symposia 2018 - [c123]Fumito Uwano, Keiki Takadama:
Ensemble Heart Rate Extraction Method for Biological Data from Water Pressure Sensor. AAAI Spring Symposia 2018 - [c122]Ryo Takano, Hiroyuki Sato, Keiki Takadama:
Artificial bee colony algorithm based on adaptive local information sharing: approach for several dynamic changes. GECCO (Companion) 2018: 95-96 - [c121]Yuta Umenai, Fumito Uwano, Hiroyuki Sato, Keiki Takadama:
Multiple swarm intelligence methods based on multiple population with sharing best solution for drastic environmental change. GECCO (Companion) 2018: 97-98 - [c120]Kazuma Matsumoto, Ryo Takano, Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
XCSR based on compressed input by deep neural network for high dimensional data. GECCO (Companion) 2018: 1418-1425 - [c119]Takato Tatsumi, Tim Kovacs, Keiki Takadama:
XCS-CR: determining accuracy of classifier by its collective reward in action set toward environment with action noise. GECCO (Companion) 2018: 1457