• 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 200 matches

• 2021
• 
  Yan Zheng, Yuanke Zhong, Jialu Hu, Xuequn Shang:
  SCC: an accurate imputation method for scRNA-seq dropouts based on a mixture model. BMC Bioinform. 22(1): 5 (2021)
• 
  Garib Nath Singh, Mohd Khalid, Jong-Min Kim:
  Some imputation methods to deal with the problems of missing data in two-occasion successive sampling. Commun. Stat. Simul. Comput. 50(2): 557-580 (2021)
• 
  Dunlu Peng, Mengping Zou, Cong Liu, Jing Lu:
  RESI: A Region-Splitting Imputation method for different types of missing data. Expert Syst. Appl. 168: 114425 (2021)
• 
  Hiroko Nagashima, Yuka Kato:
  Flexible Imputation Method for Sensor Data based on Programming by Example: APREP-S. J. Inf. Process. 29: 157-165 (2021)
• 
  Hyeonwoo Yu, Jean Oh:
  A Missing Data Imputation Method for 3D Object Reconstruction using Multi-modal Variational Autoencoder. CoRR abs/2101.10391 (2021)
• 2020
• 
  Hyundoo Jeong, Zhandong Liu:
  PRIME: a probabilistic imputation method to reduce dropout effects in single-cell RNA sequencing. Bioinform. 36(13): 4021-4029 (2020)
• 
  Burim Ramosaj, Lubna Amro, Markus Pauly:
  A cautionary tale on using imputation methods for inference in matched-pairs design. Bioinform. 36(10): 3099-3106 (2020)
• 
  Sergio Arciniegas-Alarcón, Marisol García-Peña, Paulo Canas Rodrigues:
  New multiple imputation methods for genotype-by-environment data that combine singular value decomposition and Jackknife resampling or weighting schemes. Comput. Electron. Agric. 176: 105617 (2020)
• 
  Rubul Kumar Bania, Anindya Halder:
  R-Ensembler: A greedy rough set based ensemble attribute selection algorithm with kNN imputation for classification of medical data. Comput. Methods Programs Biomed. 184: 105122 (2020)
• 
  Kyungmee Choi, Sung Min Park, Seunghoon Han, Dong-Seok Yim:
  A partial imputation EM-algorithm to adjust the overestimated shape parameter of the Weibull distribution fitted to the clinical time-to-event data. Comput. Methods Programs Biomed. 197: 105697 (2020)
• 
  Shashi Bhushan, Abhay Pratap Pandey, Arvind Pandey:
  On optimality of imputation methods for estimation of population mean using higher order moment of an auxiliary variable. Commun. Stat. Simul. Comput. 49(6): 1560-1574 (2020)
• 
  Shen-Ming Lee, T. Martin Lukusa, Chin-Shang Li:
  Estimation of a zero-inflated Poisson regression model with missing covariates via nonparametric multiple imputation methods. Comput. Stat. 35(2): 725-754 (2020)
• 
  Firouzeh Noghrehchi, Jakub Stoklosa, Spiridon I. Penev:
  Multiple imputation and functional methods in the presence of measurement error and missingness in explanatory variables. Comput. Stat. 35(3): 1291-1317 (2020)
• 
  Alexander D. Stead, Phill Wheat:
  The case for the use of multiple imputation missing data methods in stochastic frontier analysis with illustration using English local highway data. Eur. J. Oper. Res. 280(1): 59-77 (2020)
• 
  Aldi T. Kraja, E. Warwick Daw, Petra Lenzini, Lihua Wang, Shiow J. Lin, Christine A. Williams, Alan B. Wells, Kathryn L. Lunetta, Joanne M. Murabito, Paola Sebastiani, Giuseppe Tosto, Sandra Barral, Ryan L. Minster, Anatoly Yashin, Thomas Perls, Michael A. Province:
  A comparison of genetic imputation methods using Long Life Family Study genotypes and sequence data with the 1000 Genome reference panel. Int. J. Bioinform. Res. Appl. 16(1): 59-84 (2020)
• 
  Karshiev Sanjar, Olimov Bekhzod, Jaesoo Kim, Anand Paul, Jeonghong Kim:
  Missing Data Imputation for Geolocation-based Price Prediction Using KNN-MCF Method. ISPRS Int. J. Geo Inf. 9(4): 227 (2020)
• 
  Stephanie Garies, Michael Cummings, Hude Quan, Kerry A. McBrien, Neil Drummond, Donna Manca, Tyler S. Williamson:
  Methods to improve the quality of smoking records in a primary care EMR database: exploring multiple imputation and pattern-matching algorithms. BMC Medical Informatics Decis. Mak. 20(1): 56 (2020)
• 
  Zhao-Yue Chen, Jie-Qi Jin, Rong Zhang, Tian-Hao Zhang, Jin-Jian Chen, Jun Yang, Chun-Quan Ou, Yuming Guo:
  Comparison of Different Missing-Imputation Methods for MAIAC (Multiangle Implementation of Atmospheric Correction) AOD in Estimating Daily PM2.5 Levels. Remote. Sens. 12(18): 3008 (2020)
• 
  Junsheng Huang, Baohua Mao, Yun Bai, Tong Zhang, Changjun Miao:
  An Integrated Fuzzy C-Means Method for Missing Data Imputation Using Taxi GPS Data. Sensors 20(7): 1992 (2020)
• 
  Shu-Fen Huang, Ching-Hsue Cheng:
  A Safe-Region Imputation Method for Handling Medical Data with Missing Values. Symmetry 12(11): 1792 (2020)
• 
  Hariom Dhungana, Francesco Bellotti, Riccardo Berta, Alessandro De Gloria:
  Performance Comparison of Imputation Methods in Building Energy Data Sets. ApplePies 2020: 144-151
• 
  Baligh Al-Helali, Qi Chen, Bing Xue, Mengjie Zhang:
  Genetic Programming-Based Selection of Imputation Methods in Symbolic Regression with Missing Values. Australasian Conference on Artificial Intelligence 2020: 163-175
• 
  Ruiqing Zheng, Zhenlan Liang, Xiangmao Meng, Yu Tian, Min Li:
  A robust single cell clustering method based on subspace learning and partial imputation. BIBM 2020: 140-145
• 
  Mason Chen, Charles Chen:
  Optimize Neural Network Algorithm of Missing Value Imputation for Clustering Chocolate Product Types Following "STEAMS" Methodology. CATA 2020: 230-241
• 
  Edwar Macias Toro, Javier Serrano, José López Vicario, Antoni Morell:
  Novel Imputation Method Using Average Code from Autoencoders in Clinical Data. EUSIPCO 2020: 1576-1579
• 
  Lan Yang, Jason Amaro Chiang:
  Use Case and Performance Analyses for Missing Data Imputation Methods in Big Data Analytics. ICCDE 2020: 107-111
• 
  Nadav Shalit, Michael Fire, Eran Ben-Elia:
  Imputation of Missing Boarding Stop Information in Smart Card Data with Machine Learning Methods. IDEAL (1) 2020: 17-27
• 
  Yongshun Gong, Zhibin Li, Jian Zhang, Wei Liu, Bei Chen, Xiangjun Dong:
  A Spatial Missing Value Imputation Method for Multi-view Urban Statistical Data. IJCAI 2020: 1310-1316
• 
  Olga Altukhova:
  Choice of method imputation missing values for obstetrics clinical data. KES 2020: 976-984
• 
  Christos Platias, Georgios Petasis:
  A Comparison of Machine Learning Methods for Data Imputation. SETN 2020: 150-159

skipping 170 more matches