One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems
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Trung Le | Svetha Venkatesh | Tu Dinh Nguyen | Dinh Q. Phung | Vu Nguyen | S. Venkatesh | Vu Nguyen | Trung Le | T. Nguyen
[1] Trung Le,et al. Distributed data augmented support vector machine on Spark , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).
[2] Trung Le,et al. Sparkling Vector Machines , 2015 .
[3] Indre Zliobaite,et al. Learning under Concept Drift: an Overview , 2010, ArXiv.
[4] Xiaoli Z. Fern,et al. Multi-instance multi-label learning in the presence of novel class instances , 2015, ICML.
[5] Jason Weston,et al. Curriculum learning , 2009, ICML '09.
[6] Alexey Tsymbal,et al. The problem of concept drift: definitions and related work , 2004 .
[7] D. Cox. The Regression Analysis of Binary Sequences , 2017 .
[8] Gerhard Widmer,et al. Learning in the presence of concept drift and hidden contexts , 2004, Machine Learning.
[9] Cheng-Hao Tsai,et al. Large-scale logistic regression and linear support vector machines using spark , 2014, 2014 IEEE International Conference on Big Data (Big Data).
[10] Steven C. H. Hoi,et al. LIBOL: a library for online learning algorithms , 2014, J. Mach. Learn. Res..
[11] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[12] João Gama,et al. A survey on concept drift adaptation , 2014, ACM Comput. Surv..
[13] S. Canu,et al. Training Invariant Support Vector Machines using Selective Sampling , 2005 .
[14] Xin Yao,et al. DDD: A New Ensemble Approach for Dealing with Concept Drift , 2012, IEEE Transactions on Knowledge and Data Engineering.
[15] Thorsten Joachims,et al. Detecting Concept Drift with Support Vector Machines , 2000, ICML.
[16] Ameet Talwalkar,et al. MLlib: Machine Learning in Apache Spark , 2015, J. Mach. Learn. Res..
[17] James G. Scott,et al. Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables , 2012, 1205.0310.
[18] Robert H. Halstead,et al. Matrix Computations , 2011, Encyclopedia of Parallel Computing.