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Online learning represents an important family of machine learning algorithms, in which a learner attempts to resolve an online prediction (or any type of decision-making) task by learning a model/hypothesis from a sequence of data instances one at a time.
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Time Series Analysis: Forecasting & Control, 3/e
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Nick Littlestone and Manfred K. Warmuth · 1994
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Gambling in a rigged casino: The adversarial multi-armed bandit problem
Peter Auer, Nicolo Cesa-Bianchi, Yoav Freund, and Robert E Schapire · 1995
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Additive versus exponentiated gradient updates for linear prediction
Jyrki Kivinen and Manfred K. Warmuth · 1995
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Reinforcement learning: A survey
Leslie Pack Kaelbling, Michael L Littman, and Andrew W Moore · 1996
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Online learning versus offline learning
Shai Ben-David, Eyal Kushilevitz, and Yishay Mansour · 1997
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Bandit problems with infinitely many arms
Donald A Berry, Robert W Chen, Alan Zame, David C Heath, and Larry A Shepp · 1997
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A decision-theoretic generalization of on-line learning and an application to boosting
Yoav Freund and Robert E. Schapire · 1997
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Selective sampling using the query by committee algorithm
Yoav Freund, H Sebastian Seung, Eli Shamir, and Naftali Tishby · 1997
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Some label efficient learning results
David Helmbold and Sandra Panizza · 1997
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On-line algorithms in machine learning
Avrim Blum · 1998
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Multitask learning
Rich Caruana · 1998
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Forecasting economic time series
Michael Clements and David Hendry · 1998
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Online algorithms: The state of the art
Amos Fiat and Gerhard Woeginger · 1998
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On-line portfolio selection using multiplicative updates
David P Helmbold, Robert E Schapire, Yoram Singer, and Manfred K Warmuth · 1998
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Efficient backprop
Yann A LeCun, Léon Bottou, Genevieve B Orr, and Klaus-Robert Müller · 1998
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Reinforcement learning: An introduction
Richard S. Sutton and Andrew G. Barto · 1998
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Statistical learning theory , volume 1
Vladimir Naumovich Vapnik and Vlamimir Vapnik · 1998
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Universal portfolio selection
Volodya Vovk and Chris Watkins · 1998
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Support vector learning for ordinal regression
Ralf Herbrich, Thore Graepel, and Klaus Obermayer · 1999
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Fast training of support vector machines using sequential minimal optimization
John Platt et al · 1999
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An overview of statistical learning theory
Vladimir N Vapnik · 1999
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Time-series forecasting
Chris Chatfield · 2000
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Stochastic nonstationary optimization for finding universal portfolios
Alexei A Gaivoronski and Fabio Stella · 2000
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Clustering data streams
Sudipto Guha, Nina Mishra, Rajeev Motwani, and Liadan O’Callaghan · 2000
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Nonlinear dimensionality reduction by locally linear embedding
Sam T Roweis and Lawrence K Saul · 2000
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A global geometric framework for nonlinear dimensionality reduction
Joshua B Tenenbaum, Vin De Silva, and John C Langford · 2000
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Pranking with ranking
Koby Crammer, Yoram Singer, et al · 2001
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A new approximate maximal margin classification algorithm
Claudio Gentile · 2001
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Incremental and decremental support vector machine learning
Gert Cauwenberghs�Tomaso Poggio · 2001
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Learn++: An incremental learning algorithm for supervised neural networks
Robi Polikar, Lalita Upda, Satish S Upda, and Vasant Honavar · 2001
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A generalized representer theorem
Bernhard Schölkopf, Ralf Herbrich, and Alex J. Smola · 2001
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Interactive machine learning: letting users build classifiers
Malcolm Ware, Eibe Frank, Geoffrey Holmes, Mark Hall, and Ian H Witten · 2001
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Using the nyström method to speed up kernel machines
Christopher K. I. Williams and Matthias Seeger · 2001
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Using confidence bounds for exploitation-exploration trade-offs
Peter Auer · 2002
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Machine learning for sequential data: A review
Thomas G Dietterich · 2002
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The perceptron algorithm with uneven margins
Yaoyong Li, Hugo Zaragoza, Ralf Herbrich, John Shawe-Taylor, and Jaz Kandola · 2002
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The relaxed online maximum margin algorithm
Yi Li and Philip M. Long · 2002
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Streaming-data algorithms for high-quality clustering
Liadan O’callaghan, Adam Meyerson, Rajeev Motwani, Nina Mishra, and Sudipto Guha · 2002
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Online algorithms: a survey
Susanne Albers · 2003
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Learning probabilistic linear-threshold classifiers via selective sampling
Nicolò Cesa-Bianchi, Alex Conconi, and Claudio Gentile · 2003
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Online classification on a budget
Koby Crammer, Jaz S Kandola, and Yoram Singer · 2003
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Clustering data streams: Theory and practice
Sudipto Guha, Adam Meyerson, Nina Mishra, Rajeev Motwani, and Liadan O’Callaghan · 2003
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Nonparametric prediction
L Gyorfi and D Schafer · 2003
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Online ranking/collaborative filtering using the perceptron algorithm
Edward F Harrington · 2003
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Interactive machine learning system for automated annotation of information in text, July 31 2003
David Johnson, Sylvie Levesque, and Tong Zhang · 2003
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Mining concept-drifting data streams using ensemble classifiers
Haixun Wang, Wei Fan, Philip S Yu, and Jiawei Han · 2003
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M-kernel merging: Towards density estimation over data streams
Aoying Zhou, Zhiyuan Cai, Li Wei, and Weining Qian · 2003
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Semi-supervised learning using gaussian fields and harmonic functions
Xiaojin Zhu, Zoubin Ghahramani, and John D Lafferty · 2003
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Online convex programming and generalized infinitesimal gradient ascent
Martin Zinkevich · 2003
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A framework for projected clustering of high dimensional data streams
Charu C Aggarwal, Jiawei Han, Jianyong Wang, and Philip S Yu · 2004
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Fast universalization of investment strategies
Karhan Akcoglu, Petros Drineas, and Ming-Yang Kao · 2004
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Online choice of active learning algorithms
Yoram Baram, Ran El Yaniv, and Kobi Luz · 2004
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Reinforcement learning and its relationship to supervised learning
ANDREW G. BARTO and THOMAS G. DIETTERICH · 2004
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Can we learn to beat the best stock
Allan Borodin, Ran El-Yaniv, and Vincent Gogan · 2004
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Stochastic learning
Léon Bottou · 2004
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On the generalization ability of on-line learning algorithms
Nicolò Cesa-Bianchi, Alex Conconi, and Claudio Gentile · 2004
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Regularized multi–task learning
Theodoros Evgeniou and Massimiliano Pontil · 2004
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Online learning with kernels
Jyrki Kivinen, Alexander J Smola, and Robert C Williamson · 2004
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Online and batch learning of pseudo-metrics
Shai Shalev-Shwartz, Yoram Singer, and Andrew Y Ng · 2004
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Solving large scale linear prediction problems using stochastic gradient descent algorithms
Tong Zhang · 2004
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Online ranking by projecting
Koby Crammer and Yoram Singer · 2005
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The forgetron: A kernel-based perceptron on a fixed budget
Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer · 2005
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An incremental data stream clustering algorithm based on dense units detection
Jing Gao, Jianzhong Li, Zhaogong Zhang, and Pang-Ning Tan · 2005
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Efficient algorithms for online decision problems
Adam Tauman Kalai and Santosh Vempala · 2005
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Learning to rank
Andrew Trotman · 2005
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Multi-armed bandit algorithms and empirical evaluation
Joannes Vermorel and Mehryar Mohri · 2005
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Online (and offline) on an even tighter budget
Jason Weston, Antoine Bordes, Léon Bottou, et al · 2005
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Data dependent concentration bounds for sequential prediction algorithms
Tong Zhang · 2005
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Algorithms for portfolio management based on the newton method
Amit Agarwal, Elad Hazan, Satyen Kale, and Robert E Schapire · 2006
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Manifold regularization: A geometric framework for learning from labeled and unlabeled examples
Mikhail Belkin, Partha Niyogi, and Vikas Sindhwani · 2006
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A survey of clustering data mining techniques
Pavel Berkhin · 2006
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Density-based clustering over an evolving data stream with noise
Feng Cao, Martin Ester, Weining Qian, and Aoying Zhou · 2006
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Prediction, learning, and games
Nicolò Cesa-Bianchi and Gábor Lugosi · 2006
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Worst-case analysis of selective sampling for linear classification
Nicolò Cesa-Bianchi, Claudio Gentile, and Luca Zaniboni · 2006
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Online passive-aggressive algorithms
Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, and Yoram Singer · 2006
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Online multitask learning
Ofer Dekel, Philip M Long, and Yoram Singer · 2006
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Two view learning: Svm-2k, theory and practice
Jason Farquhar, David Hardoon, Hongying Meng, John S Shawe-taylor, and Sandor Szedmak · 2006
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Incremental nonlinear dimensionality reduction by manifold learning
Martin HC Law and Anil K Jain · 2006
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A fast and accurate online sequential learning algorithm for feedforward networks
Nan-Ying Liang, Guang-Bin Huang, Paramasivan Saratchandran, and Narasimhan Sundararajan · 2006
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Large scale multiple kernel learning
Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer, and Bernhard Schölkopf · 2006
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Distance metric learning: A comprehensive survey
Liu Yang and Rong Jin · 2006
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Semi-supervised learning literature survey
Xiaojin Zhu · 2006
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Online collaborative filtering
Jacob Abernethy, Kevin Canini, John Langford, and Alex Simma · 2007
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Detecting distance-based outliers in streams of data
Fabrizio Angiulli and Fabio Fassetti · 2007
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Predicting structured data
Gökhan BakIr · 2007
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Learning to rank: from pairwise approach to listwise approach
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, and Hang Li · 2007
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Tracking the best hyperplane with a simple budget perceptron
Giovanni Cavallanti, Nicolò Cesa-Bianchi, and Claudio Gentile · 2007
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Density-based clustering for real-time stream data
Yixin Chen and Li Tu · 2007
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Google news personalization: scalable online collaborative filtering
Abhinandan S Das, Mayur Datar, Ashutosh Garg, and Shyam Rajaram · 2007
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Information-theoretic metric learning
Jason V Davis, Brian Kulis, Prateek Jain, Suvrit Sra, and Inderjit S Dhillon · 2007
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Online kernel pca with entropic matrix updates
Dima Kuzmin and Manfred K Warmuth · 2007
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Vowpal wabbit online learning project, 2007
John Langford, Lihong Li, and Alex Strehl · 2007
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Algorithmic game theory , volume 1
Noam Nisan, Tim Roughgarden, Eva Tardos, and Vijay V Vazirani · 2007
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Random features for large-scale kernel machines
Ali Rahimi and Benjamin Recht · 2007
Cited alongside, same era.
Online learning: Theory, algorithms, and applications
Shai Shalev-Shwartz · 2007
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A primal-dual perspective of online learning algorithms
Shai Shalev-Shwartz and Yoram Singer · 2007
Cited alongside, same era.
Visualising the cluster structure of data streams
Dimitris K Tasoulis, Gordon Ross, and Niall M Adams · 2007
Cited alongside, same era.
Competing in the dark: An efficient algorithm for bandit linear optimization
Jacob Abernethy, Elad Hazan, and Alexander Rakhlin · 2008
Cited alongside, same era.
A framework for estimating complex probability density structures in data streams
Arnold P Boedihardjo, Chang-Tien Lu, and Feng Chen · 2008
Cited alongside, same era.
Online feature selection for mining big data
Steven CH Hoi, Jialei Wang, Peilin Zhao, and Rong Jin · 2012
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Online kernel principal component analysis: A reduced-order model
Paul Honeine · 2012
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On bayesian upper confidence bounds for bandit problems
Emilie Kaufmann, Olivier Cappé, and Aurélien Garivier · 2012
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Security analysis of online centroid anomaly detection
Marius Kloft and Pavel Laskov · 2012
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Learning task grouping and overlap in multi-task learning
Abhishek Kumar and Hal Daumé III · 2012
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On-line portfolio selection with moving average reversion
Bin Li and Steven CH Hoi · 2012
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The tradeoffs of large scale learning
Olivier Bousquet and Léon Bottou · 2008
Cited alongside, same era.
Improved risk tail bounds for on-line algorithms
Nicolò Cesa-Bianchi and Claudio Gentile · 2008
Cited alongside, same era.
Active learning with confidence
Mark Dredze and Koby Crammer · 2008
Cited alongside, same era.
Confidence-weighted linear classification
Mark Dredze, Koby Crammer, and Fernando Pereira · 2008
Cited alongside, same era.
Online manifold regularization: A new learning setting and empirical study
Andrew B Goldberg, Ming Li, and Xiaojin Zhu · 2008
Cited alongside, same era.
Nonparametric nearest neighbor based empirical portfolio selection strategies
László Györfi, Frederic Udina, and Harro Walk · 2008
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Pamr: Passive aggressive mean reversion strategy for portfolio selection
Bin Li, Peilin Zhao, Steven CH Hoi, and Vivekanand Gopalkrishnan · 2012
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Online learning for collaborative filtering
Guang Ling, Haiqin Yang, Irwin King, and Michael R Lyu · 2012
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Optimistic bayesian sampling in contextual-bandit problems
Benedict C May, Nathan Korda, Anthony Lee, and David S Leslie · 2012
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Two-view online learning
Tam T Nguyen, Kuiyu Chang, and Siu Cheung Hui · 2012
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Density-based projected clustering over high dimensional data streams
Irene Ntoutsi, Arthur Zimek, Themis Palpanas, Peer Kröger, and Hans-Peter Kriegel · 2012
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Batch-incremental versus instance-incremental learning in dynamic and evolving data
Jesse Read, Albert Bifet, Bernhard Pfahringer, and Geoff Holmes · 2012
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Leveraging over prior knowledge for online learning of visual categories
Tatiana Tommasi, Francesco Orabona, Mohsen Kaboli, Barbara Caputo, and CH Martigny · 2012
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Density-based hierarchical clustering for streaming data
Q Tu, JF Lu, B Yuan, JB Tang, and Jing-Yu Yang · 2012
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Online alternating direction method
Huahua Wang and Arindam Banerjee · 2012
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Online kernel selection: Algorithms and evaluations
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, and Steven CH Hoi · 2012
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Efficient online learning for large-scale sparse kernel logistic regression
Lijun Zhang, Rong Jin, Chun Chen, Jiajun Bu, and Xiaofei He · 2012
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Bduol: double updating online learning on a fixed budget
Peilin Zhao and Steven CH Hoi · 2012
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Fast bounded online gradient descent algorithms for scalable kernel-based online learning
Peilin Zhao, Jialei Wang, Pengcheng Wu, Rong Jin, and Steven C. H. Hoi · 2012
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A survey of stream clustering algorithms., 2013
Charu C Aggarwal · 2013
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Thompson sampling for contextual bandits with linear payoffs
Shipra Agrawal and Navin Goyal · 2013
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Online learning for time series prediction
Oren Anava, Elad Hazan, Shie Mannor, and Ohad Shamir · 2013
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Stochastic optimization of pca with capped msg
Raman Arora, Andy Cotter, and Nati Srebro · 2013
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Efficient transductive online learning via randomized rounding
Nicolò Cesa-Bianchi and Ohad Shamir · 2013
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Online pca for contaminated data
Jiashi Feng, Huan Xu, Shie Mannor, and Shuicheng Yan · 2013
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One-pass auc optimization
Wei Gao, Rong Jin, Shenghuo Zhu, and Zhi-Hua Zhou · 2013
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Oms-tl: a framework of online multiple source transfer learning
Liang Ge, Jing Gao, and Aidong Zhang · 2013
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Online multiple kernel classification
Steven C. H. Hoi, Rong Jin, Peilin Zhao, and Tianbao Yang · 2013
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Robust median reversion strategy for on-line portfolio selection
Dingjiang Huang, Junlong Zhou, Bin Li, Steven CH Hoi, and Shuigeng Zhou · 2013
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On the generalization ability of online learning algorithms for pairwise loss functions
Purushottam Kar, Bharath K Sriperumbudur, Prateek Jain, and Harish C Karnick · 2013
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Online Portfolio Selection
Bin Li · 2013
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Confidence weighted mean reversion strategy for online portfolio selection
Bin Li, Steven CH Hoi, Peilin Zhao, and Vivekanand Gopalkrishnan · 2013
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Second order online collaborative filtering
Jing Lu, Steven Hoi, and Jialei Wang · 2013
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Memory limited, streaming pca
Ioannis Mitliagkas, Constantine Caramanis, and Prateek Jain · 2013
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D-admm: A communication-efficient distributed algorithm for separable optimization
João FC Mota, João MF Xavier, Pedro MQ Aguiar, and Markus Püschel · 2013
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Performance analysis of log-optimal portfolio strategies with transaction costs
Mihály Ormos and András Urbán · 2013
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Ella: An efficient lifelong learning algorithm
Paul Ruvolo and Eric Eaton · 2013
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Lifelong machine learning systems: Beyond learning algorithms
Daniel L Silver, Qiang Yang, and Lianghao Li · 2013
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A survey of multi-view machine learning
Shiliang Sun · 2013
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Online multimodal deep similarity learning with application to image retrieval
Pengcheng Wu, Steven CH Hoi, Hao Xia, Peilin Zhao, Dayong Wang, and Chunyan Miao · 2013
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Online multi-modal distance learning for scalable multimedia retrieval
Hao Xia, Pengcheng Wu, and Steven CH Hoi · 2013
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A survey on multi-view learning
Chang Xu, Dacheng Tao, and Chao Xu · 2013
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Kernel Based Online Learning
Peilin Zhao · 2013
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Cost-sensitive online active learning with application to malicious url detection
Peilin Zhao and Steven CH Hoi · 2013
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Active learning with expert advice
Peilin Zhao, Steven C. H. Hoi, and Jinfeng Zhuang · 2013
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Quality and efficiency for kernel density estimates in large data
Yan Zheng, Jeffrey Jestes, Jeff M Phillips, and Feifei Li · 2013
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On density-based data streams clustering algorithms: A survey
Amineh Amini, Teh Ying Wah, and Hadi Saboohi · 2014
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Clustering data streams using grid-based synopsis
Vasudha Bhatnagar, Sharanjit Kaur, and Sharma Chakravarthy · 2014
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Improving cross-resolution face matching using ensemble based co-transfer learning
H Bhatt, Richa Singh, Mayank Vatsa, and N Ratha · 2014
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Soml: Sparse online metric learning with application to image retrieval
Xingyu Gao, Steven CH Hoi, Yongdong Zhang, Ji Wan, and Jintao Li · 2014
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On handling negative transfer and imbalanced distributions in multiple source transfer learning
Liang Ge, Jing Gao, Hung Ngo, Kang Li, and Aidong Zhang · 2014
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Outlier detection for temporal data: A survey
Manish Gupta, Jing Gao, Charu C Aggarwal, and Jiawei Han · 2014
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Libol: a library for online learning algorithms
Steven CH Hoi, Jialei Wang, and Peilin Zhao · 2014
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Online portfolio selection: A survey
Bin Li and Steven CH Hoi · 2014
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Collaborative online multitask learning
Guangxia Li, Steven CH Hoi, Kuiyu Chang, Wenting Liu, and Ramesh Jain · 2014
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Online passive aggressive active learning and its applications
Jing Lu, Peilin Zhao, and Steven C.H. Hoi · 2014
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Lipschitz bandits: Regret lower bound and optimal algorithms
Stefan Magureanu, Richard Combes, and Alexandre Proutière · 2014
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Online multiple kernel regression
Doyen Sahoo, Steven CH Hoi, and Bin Li · 2014
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Collaborative filtering beyond the user-item matrix: A survey of the state of the art and future challenges
Yue Shi, Martha Larson, and Alan Hanjalic · 2014
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High-dimensional data stream classification via sparse online learning
Dayong Wang, Pengcheng Wu, Peilin Zhao, Yue Wu, Chunyan Miao, and Steven CH Hoi · 2014
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Massive-scale online feature selection for sparse ultra-high dimensional data
Yue Wu, Steven CH Hoi, and Tao Mei · 2014
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Online multiple kernel similarity learning for visual search
Hao Xia, Steven CH Hoi, Rong Jin, and Peilin Zhao · 2014
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Accelerated online learning for collaborative filtering and recommender systems
Li Yuan-Xiang, Li Zhi-Jie, Wang Feng, and Kuang Li · 2014
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Online transfer learning
Peilin Zhao, Steven CH Hoi, Jialei Wang, and Bin Li · 2014
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Simapp: A framework for detecting similar mobile applications by online kernel learning
Ning Chen, Steven CH Hoi, Shaohua Li, and Xiaokui Xiao · 2015
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Combinatorial bandits revisited
Richard Combes, Mohammad Sadegh Talebi Mazraeh Shahi, Alexandre Proutiere, et al · 2015
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An adaptive gradient method for online auc maximization
Yi Ding, Peilin Zhao, Steven CH Hoi, and Yew-Soon Ong · 2015
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Active crowdsourcing for annotation
Shuji Hao, Steven CH Hoi, Chunyan Miao, and Peilin Zhao · 2015
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Kernelized online imbalanced learning with fixed budgets
Junjie Hu, Haiqin Yang, Irwin King, Michael R Lyu, and Anthony Man-Cho So · 2015
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Semi-universal portfolios with transaction costs
Dingjiang Huang, Yan Zhu, Bin Li, Shuigeng Zhou, and Steven CH Hoi · 2015
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Second-order quantile methods for experts and combinatorial games
Wouter M Koolen and Tim Van Erven · 2015
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Online Portfolio Selection: Principles and Algorithms
Bin Li and Steven Chu Hong Hoi · 2015
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Moving average reversion strategy for on-line portfolio selection
Bin Li, Steven CH Hoi, Doyen Sahoo, and Zhi-Yong Liu · 2015
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Large scale online kernel learning
Jing Lu, Steven C.H. Hoi, Jialei Wang, Peilin Zhao, and Zhi-Yong Liu · 2015
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Achieving all with no parameters: Adanormalhedge
Haipeng Luo and Robert E Schapire · 2015
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Multivariate density estimation: theory, practice, and visualization
David W Scott · 2015
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Online learning to rank for content-based image retrieval
Ji Wan, Pengcheng Wu, Steven CH Hoi, Peilin Zhao, Xingyu Gao, Dayong Wang, Yongdong Zhang, and Jintao Li · 2015
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Cost-sensitive online classification with adaptive regularization and its applications
Peilin Zhao, Furen Zhuang, Min Wu, Xiao-Li Li, and Steven CH Hoi · 2015
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A survey on contextual multi-armed bandits
Li Zhou · 2015
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Online convex optimization with unconstrained domains and losses
Ashok Cutkosky and Kwabena A Boahen · 2016
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Soal: Second-order online active learning
Shuji Hao, Peilin Zhao, Jing Lu, Steven CH Hoi, Chunyan Miao, and Chi Zhang · 2016
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