Learning from Time Series in the Presence of Noise: Unsupervised and Semi-Supervised Approaches

Learning from Time Series in the Presence of Noise: Unsupervised and Semi-Supervised Approaches (2008)

Cached

Download Links

[www.cs.ucr.edu]

by Dragomir Dimitrov Yankov

BibTeX

@MISC{Yankov08learningfrom,
    author = {Dragomir Dimitrov Yankov},
    title = {Learning from Time Series in the Presence of Noise: Unsupervised and Semi-Supervised Approaches},
    year = {2008}
}

Bookmark

OpenURL

Abstract

Citations

6694	Statistical Learning Theory - Vapnik - 1998
1568	Density Estimation for Statistics and Data Analysis - Silverman - 1986
1511	Online learning with kernels - Kivinen, Smola, et al.
1228	A global geometric framework for nonlinear dimensionality reduction - Tenenbaum, Silva, et al. - 2000
1156	Nonlinear dimensionality reduction by locally linear embedding - Roweis, Saul - 2000
913	MapReduce: Simplified data processing on large clusters - Dean, Ghemawat
850	Shape matching and object recognition using shape contexts - Belongie, Malik, et al. - 2002
775	Nonlinear component analysis as a kernel eigenvalue problem - Schölkopf, Smola, et al. - 1998
756	On spectral clusterings: Analysis and an algorithm - Ng, Jordan, et al. - 2002
519	Laplacian eigenmaps for dimensionality reduction and data representation - Belkin, Niyogi - 2003
509	Transductive inference for text classification using support vector machines - Joachims - 1999
381	Estimating the support of a high-dimensional distribution - Schölkopf, Platt, et al. - 2001
372	Fast subsequence matching in time-series databases - Faloutsos, Ranganathan, et al. - 1994
294	Algebraic connectivity of graphs - Fiedler - 1973
290	Image retrieval: current techniques, promising directions and open issues - Rui, Huang, et al. - 1999
225	Data structures and algorithms for nearest neighbor search in general metric spaces - Yianilos - 1993
214	LOF: identifying density-based local outliers - Breunig, Kriegel, et al.
208	Algorithms for mining distance-based outliers in large datasets - Knorr, Ng - 1998
205	Time Series Prediction: Forecasting the Future and Understanding the Past - Weigend, Gershenfeld - 1993
197	G: The EM algorithm for mixtures of factor analyzers - Ghahramani, Hinton - 1997
187	Hierarchical chamfer matching: a parametric edge matching algorithm - Borgefors - 1988
177	A cost model for nearest neighbor search in high-dimensional data space - Berchtold, Böhm, et al. - 1997
171	Semi-Supervised Learning - Chapelle, Schlkopf, et al. - 2006
169	On the need for time series data mining benchmarks: A survey and empirical demonstration - Keogh, Kasetty - 2002
146	Semi-supervised support vector machines - Bennet, Demiriz - 1998
124	Support vector clustering - Ben-Hur, Horn, et al. - 2001
120	M.: Variational inference for Bayesian mixtures of factor analysers - Ghahramani, Beal - 2000
117	Some approaches to best-match file searching - Burkhard, Keller - 1973
117	D.: Shape distributions - Osada, Funkhouser, et al. - 2002
116	Clustering with instance-level constraints - Wagstaff, Cardie - 2000
112	Efficient and robust retrieval by shape content through curvature scale space - Mokhtarian, Abbasi, et al. - 1997
93	Review of shape representation and description techniques,pattern recognition - Zhang, Lu - 2004
92	Exact discovery of time series motifs - Mueen, Keogh, et al. - 2009
90	Training with noise is equivalent to Tikhonov regularization - Bishop - 1995
89	Semi-supervised classification by low density separation - Chapelle, Zien - 2005
87	Content-Based Image Retrieval Systems: A Survey,” Univ - Veltkamp, Tanase
84	Mining distance-based outliers in near linear time with randomization and a simple pruning rule - Bay, Schwabacher - 2003
80	Analysis of planar shapes using geodesic paths on shape spaces - Klassen, Srivastava, et al. - 2002
77	Automatic target recognition by matching oriented edge pixels - Olson, Huttenlocher - 1997
75	J.C.: Support vector method for novelty detection - Scholkopf, Williamson, et al.
63	Global coordination of local linear models - Roweis, Saul, et al. - 2002
58	Clustering of time-series subsequences is meaningless: implications for previous and future research. Knowl Inf Syst 8(2):154–177 - EJ, Lin - 2005
55	Support vector data description - Tax, Duin
45	A unifying theorem for spectral embedding and clustering - Brand, Huang - 2003
45	On two geometric problems related to the travelling salesman problem - Papadimitriou, Vazirani - 1984
43	HOT SAX: Efficient finding the most unusual time series subsequence - Keogh, Lin, et al. - 2005
42	The isomap algorithm and topological stability - Balasubramanian, Schwartz, et al.
35	Mining deviants in a time series database - Jagadish, Koudas, et al. - 1999
35	An index-based approach for similarity search supporting time warping in large sequence databases - Kim, Park, et al. - 2001
35	The choice of reference points in best-match file searching - Shapiro - 1977