• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 25 matches

• 2024
• 
  Yilin Lei, Ao Lin, Jianuo Cao:
  Rhythms of Victory: Predicting Professional Tennis Matches Using Machine Learning. IEEE Access 12: 113608-113617 (2024)
• 
  Shiquan Ling, Yanglang Yuan, Danqi Yan, Yuquan Leng, Yiming Rong, George Q. Huang:
  RHYTHMS: Real-time Data-driven Human-machine Synchronization for Proactive Ergonomic Risk Mitigation in the Context of Industry 4.0 and Beyond. Robotics Comput. Integr. Manuf. 87: 102709 (2024)
• 
  Fernando Gualda:
  Bits and Beats: Computing Rhythmic Information as Bitwise Operations Optimized for Machine Learning. MCM 2024: 393-404
• 
  Zhongju Yuan, Wannes Van Ransbeeck, Geraint A. Wiggins, Dick Botteldooren:
  A Dynamic Systems Approach to Modelling Human-Machine Rhythm Interaction. CoRR abs/2407.09538 (2024)
• 2023
• 
  Sergey V. Stasenko, Andrey Kovalchuk, Eremin Evgeny, Olga V. Drugova, Natalya Zarechnova, Maria Tsirkova, Sergey Permyakov, Sergey Parin, Sofia Polevaya:
  Using Machine Learning Algorithms to Determine the Post-COVID State of a Person by Their Rhythmogram. Sensors 23(11): 5272 (2023)
• 
  Paul Samuel Ignacio:
  Detection of Fibrillatory Episodes in Atrial Fibrillation Rhythms via Topology-informed Machine Learning. ICMVA 2023
• 
  Holly Hunter, Jamie Payton, Christine Julien:
  Expanding Elementary School Computer Science Education with an Introduction to Machine Learning Through Rhythmic Studies. MobiHoc 2023: 463-467
• 2022
• 
  Sergey V. Stasenko, Andrey Kovalchuk, Eremin Evgeny, Natalya Zarechnova, Maria Tsirkova, Sergey Permyakov, Sergey Parin, Sofia Polevaya:
  Using machine learning algorithms to determine the post-COVID state of a person by his rhythmogram. CoRR abs/2212.13878 (2022)
• 
  Sergey V. Stasenko, Olga Shemagina, Eremin Evgeny, Vladimir G. Yakhno, Sergey Parin, Sofia Polevaya:
  Using machine learning algorithms to determine the emotional disadaptation of a person by his rhythmogram. CoRR abs/2212.13895 (2022)
• 2021
• 
  Damodar Panigrahy, Prasanna Kumar Sahu, Felix Albu:
  Detection of ventricular fibrillation rhythm by using boosted support vector machine with an optimal variable combination. Comput. Electr. Eng. 91: 107035 (2021)
• 
  Hui Wang, Lei Zhang, Longxu Yao:
  Application of genetic algorithm based support vector machine in selection of new EEG rhythms for drowsiness detection. Expert Syst. Appl. 171: 114634 (2021)
• 
  Fiaz Majeed, Muhammad Asim, Syed Ali Abbas, Abdul Jaleel, Abdul Majid, Muhammad Awais Hassan, Fayyaz Ahmad, Muhammad Shafiq:
  Detection of Atrial Fibrillation and Normal Sinus Rhythm Using Multiple Machine Learning Classifiers. J. Medical Imaging Health Informatics 11(5): 1453-1462 (2021)
• 2020
• 
  Robert Czabanski, Krzysztof Horoba, Janusz Wrobel, Adam Matonia, Radek Martinek, Tomasz Kupka, Michal Jezewski, Radana Kahankova, Janusz Jezewski, Jacek M. Leski:
  Detection of Atrial Fibrillation Episodes in Long-Term Heart Rhythm Signals Using a Support Vector Machine. Sensors 20(3): 765 (2020)
• 2019
• 
  Juan A. Barios, Santiago Ezquerro, Arturo Bertomeu-Motos, Marius Nann, Francisco Javier Badesa, Eduardo Fernández, Surjo R. Soekadar, Nicolás García Aracil:
  Synchronization of Slow Cortical Rhythms During Motor Imagery-Based Brain-Machine Interface Control. Int. J. Neural Syst. 29(5): 1850045:1-1850045:14 (2019)
• 
  Sang-Eon Park, Nealen G. Laxpati, Claire-Anne Gutekunst, Mark J. Connolly, Jack Tung, Ken Berglund, Babak Mahmoudi, Robert E. Gross:
  A Machine Learning Approach to Characterize the Modulation of the Hippocampal Rhythms Via Optogenetic Stimulation of the Medial Septum. Int. J. Neural Syst. 29(10): 1950020:1-1950020:21 (2019)
• 
  Iraia Isasi, Unai Irusta, Andoni Elola, Elisabete Aramendi, Trygve Eftestøl, Jo Kramer-Johansen, Lars Wik:
  A Robust Machine Learning Architecture for a Reliable ECG Rhythm Analysis during CPR. EMBC 2019: 1903-1907
• 
  Marat Bogdanov, Salim Baigildin, Aygul Fabarisova, Konstantin Ushenin, Olga Solovyova:
  Effects of lead position, cardiac rhythm variation and drug-induced QT prolongation on performance of machine learning methods for ECG processing. CoRR abs/1912.04672 (2019)
• 2018
• 
  Minh Tuan Nguyen, Ahsan Shahzad, Binh Van Nguyen, Kiseon Kim:
  Diagnosis of shockable rhythms for automated external defibrillators using a reliable support vector machine classifier. Biomed. Signal Process. Control. 44: 258-269 (2018)
• 2017
• 
  Chengyu Liu, Qiao Li, Pradyumna B. Suresha, Gari D. Clifford:
  Combining Multi-source Features and Support Vector Machine for Heart Rhythm Classification. CinC 2017
• 2016
• 
  Reinmar J. Kobler, Reinhold Scherer:
  Restricted Boltzmann Machines in Sensory Motor Rhythm Brain-Computer Interfacing: A study on inter-subject transfer and co-adaptation. SMC 2016: 469-474
• 2010
• 
  Kevin Gold, Alexandra Olivier:
  Using Machine Translation to Convert Between Difficulties in Rhythm Games. AIIDE 2010
• 2007
• 
  James Bo Begole, John C. Tang:
  Incorporating Human and Machine Interpretation of Unavailability and Rhythm Awareness Into the Design of Collaborative Applications. Hum. Comput. Interact. 22(1-2): 7-45 (2007)
• 2005
• 
  Bozena Kostek, Jaroslaw Wójcik:
  Machine learning system for estimating the rhythmic salience of sounds. Int. J. Knowl. Based Intell. Eng. Syst. 9(4): 275-284 (2005)
• 1996
• 
  Teresa Zielinska:
  Coupled oscillators utilised as gait rhythm generators of a two-legged walking machine. Biol. Cybern. 74(3): 263-273 (1996)
• 1994
• 
  David Rosenthal:
  Machine Rhythm. AAAI 1994: 1508