-
1
-
-
0000068589
-
The making of maximum likelihood 1912-1922
-
J. Aldrich, R.A. Fisher and the making of maximum likelihood 1912-1922, Statistical Science, 12(3), 1922.
-
(1922)
Statistical Science
, vol.12
, Issue.3
-
-
Aldrich, J.1
Fisher, R.A.2
-
2
-
-
0032280519
-
Boosting the margin: A new explanation for the effective of voting methods
-
p. Bartlett, Y. Freund, W. Lee and R. Schapire, Boosting the Margin: A New Explanation for the Effective of Voting methods, The Annals of Statistics, vol(26),1998.
-
(1998)
The Annals of Statistics
, vol.26
-
-
Bartlett, P.1
Freund, Y.2
Lee, W.3
Schapire, R.4
-
3
-
-
0001931577
-
An empirical comparison of voting classification algorithms: Bagging, boosting and variants
-
E. Bauer and R. Kohavi, An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting and Variants, Journal of Machine Learning, 1998.
-
(1998)
Journal of Machine Learning
-
-
Bauer, E.1
Kohavi, R.2
-
4
-
-
77951191695
-
Audio classification of bird species: A statistical manifold approach
-
F. Briggs, R. Raich and X. Fern, Audio Classification of Bird Species: a Statistical Manifold Approach, ICDM, 2009.
-
(2009)
ICDM
-
-
Briggs, F.1
Raich, R.2
Fern, X.3
-
8
-
-
84964561483
-
DTW-D, Time series semi-supervised learning from a single example
-
Y. Chen, B. Hu, E. Keogh and G. E.A.p. A Batista, DTW-D, Time Series Semi-Supervised Learning from a Single Example, KDD, 2013
-
(2013)
KDD
-
-
Chen, Y.1
Hu, B.2
Keogh, E.3
Batista, G.E.A.P.A.4
-
9
-
-
84867136666
-
Querying and mining of time series data: Experimental comparison of representations and distance measures
-
H. Ding, G. Trajcevski, p. Scheuermann, X. Wang and E. Keogh, Querying and Mining of Time Series Data: Experimental Comparison of Representations and Distance Measures, PVLDB 1(2): 1542-1552, 2008.
-
(2008)
PVLDB
, vol.1
, Issue.2
, pp. 1542-1552
-
-
Ding, H.1
Trajcevski, G.2
Scheuermann, P.3
Wang, X.4
Keogh, E.5
-
10
-
-
0031269184
-
Beyond independence: Condition for the optimality of thhe simple bayesian classifier
-
p. Domingos and M. Pazzani, Beyond Independence: Condition for the Optimality of thhe Simple Bayesian Classifier, Machine Learning, vol(29), p(103-137), 1997.
-
(1997)
Machine Learning
, vol.29
, pp. 103-137
-
-
Domingos, P.1
Pazzani, M.2
-
11
-
-
84894674548
-
-
Digital Interaction at Culture Lab, accessed on Jan 9
-
Digital Interaction at Culture Lab, di.ncl.ac.uk/publicweb/Ambient Kitchen/, accessed on Jan 9, 2013.
-
(2013)
-
-
-
14
-
-
84866030149
-
Subspace correlation clustering: Finding locally correlated dimensions in subspace projections of the data
-
S. Günnemann, I. Färber, K. Virochsiri, and T. Seidl, Subspace Correlation Clustering: Finding Locally Correlated Dimensions in Subspace Projections of the Data, KDD, 2012.
-
(2012)
KDD
-
-
Günnemann, S.1
Färber, I.2
Virochsiri, K.3
Seidl, T.4
-
15
-
-
84960076541
-
Time series classification under more realistic assumptions
-
B. Hu, Y. Chen and E. Keogh, Time Series Classification under More Realistic Assumptions, SDM, 2013.
-
(2013)
SDM
-
-
Hu, B.1
Chen, Y.2
Keogh, E.3
-
16
-
-
84857158294
-
Discovering the Intrinsic Cardinality and Dimensionality of Time Series using MDL
-
B. Hu, T. Rakthanmanon, Y. Hao, S. Evans, S. Lonardi, E. Keogh, Discovering the Intrinsic Cardinality and Dimensionality of Time Series using MDL, ICDM, 2011
-
(2011)
ICDM
-
-
Hu, B.1
Rakthanmanon, T.2
Hao, Y.3
Evans, S.4
Lonardi, S.5
Keogh, E.6
-
19
-
-
38049149222
-
-
Homepage
-
E. Keogh, Q. Zhu, B. Hu, Y. Hao, X. Xi, L. Wei and C.A. Ratanamahatana. The UCR Time Series Classification/Clustering Homepage: www.cs..ucr.edu/~eamonn/ time-series-data/, 2006.
-
(2006)
The UCR Time Series Classification/Clustering
-
-
Keogh, E.1
Zhu, Q.2
Hu, B.3
Hao, Y.4
Xi, X.5
Wei, L.6
Ratanamahatana, C.A.7
-
20
-
-
84874097930
-
Mining of temporal coherent subspace clusters in multivariate time series databases
-
H. Kremer, S. Günnemann, A. Held and T. Seidl, Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases, PAKDD, 2012.
-
(2012)
PAKDD
-
-
Kremer, H.1
Günnemann, S.2
Held, A.3
Seidl, T.4
-
22
-
-
78149292125
-
Dynamic weighted majority: A new ensemble method for tracking concept drift
-
J. Kolter and M. Maloof, Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift, ICDM, 2003.
-
(2003)
ICDM
-
-
Kolter, J.1
Maloof, M.2
-
23
-
-
77951101947
-
A $3 gesture recognizer -simple gesture recognition for devices equipped with 3d acceleration sensors
-
S. Kratz and M. Rohs, A $3 Gesture Recognizer -Simple Gesture Recognition for Devices Equipped with 3D Acceleration Sensors, IUI, 2010.
-
(2010)
IUI
-
-
Kratz, S.1
Rohs, M.2
-
27
-
-
30744462795
-
Activity classification using realistic data from wearable sensors
-
J. Pärkkä, M. Ermes, p. Korpipää, J. Mäntyjärvi, J. Peltola, and I. K Korhonen, Activity classification using realistic data from wearable sensors, IEEE Trans. Inf. Tech. Biomed., vol. 10, pp. 119-28, 2006.
-
(2006)
IEEE Trans. Inf. Tech. Biomed.
, vol.10
, pp. 119-128
-
-
Pärkkä, J.1
Ermes, M.2
Korpipää, P.3
Mäntyjärvi, J.4
Peltola, J.5
Korhonen, I.K.6
-
28
-
-
0033281701
-
Improved boosting algorithms using confidence-rated predictions
-
R.E. Schapire, and Y. Singer, Improved Boosting Algorithms using Confidence-rated Predictions, Journal of Machine Learning, 1999.
-
(1999)
Journal of Machine Learning
-
-
Schapire, R.E.1
Singer, Y.2
-
29
-
-
0346660758
-
A streaming ensemble algorithm (SEA) for large-scale classification
-
W. Street and Y. Kim, A Streaming Ensemble Algorithm (SEA) for Large-Scale Classification, KDD, 2001.
-
(2001)
KDD
-
-
Street, W.1
Kim, Y.2
-
31
-
-
0000476855
-
Feature selection for ensembles
-
D. Optitz, Feature Selection for Ensembles, AAAI, 1999
-
(1999)
AAAI
-
-
Optitz, D.1
-
32
-
-
84879888269
-
Time series classification in many intrinsic dimensions
-
M. Radovanović, A. Nanopoulos and M. Ivanović, Time Series Classification in Many Intrinsic Dimensions, SDM, 2010.
-
(2010)
SDM
-
-
Radovanović, M.1
Nanopoulos, A.2
Ivanović, M.3
-
34
-
-
84055192810
-
Introducing a modular activity monitoring system
-
A. Reiss and D. Stricker, Introducing a Modular Activity Monitoring System, 33rd IEEE EMBS,2011.
-
(2011)
33rd IEEE EMBS
-
-
Reiss, A.1
Stricker, D.2
-
36
-
-
77952414056
-
Indexing multi-dimensional time series with support for multiple distance measures
-
M. Vlachos, M. Hadjieleftheriou, D. Gunopulos and E. Keogh, Indexing Multi-Dimensional Time Series with Support for Multiple Distance Measures, KDD, 2003.
-
(2003)
KDD
-
-
Vlachos, M.1
Hadjieleftheriou, M.2
Gunopulos, D.3
Keogh, E.4
-
37
-
-
33749260341
-
Fast time series classification using numerosity reduction
-
X. Xi, E. Keogh, C. Shelton, L. Wei and C. Ratanamahatana, Fast Time Series Classification Using Numerosity Reduction, ICML, 2006.
-
(2006)
ICML
-
-
Xi, X.1
Keogh, E.2
Shelton, C.3
Wei, L.4
Ratanamahatana, C.5
-
39
-
-
84872397385
-
Experimental comparison of representation methods and distance measures for time series data
-
X. Wang, A. Mueen, H. Ding, G. Trajcevski, p. Scheuermann, E. Keogh, Experimental comparison of representation methods and distance measures for time series data. DMKD, vol26(2), 2013.
-
(2013)
DMKD
, vol.26
, Issue.2
-
-
Wang, X.1
Mueen, A.2
Ding, H.3
Trajcevski, G.4
Scheuermann, P.5
Keogh, E.6
-
40
-
-
33645471785
-
Feature subset selection and feature ranking for multivariate time series
-
H. Yoon, K. Yang, C. Shahabi, Feature Subset Selection and Feature Ranking for Multivariate Time Series, IEEE Trans. Knowl. Data Eng. 17(9): 1186-1198, 2005.
-
(2005)
IEEE Trans. Knowl. Data Eng.
, vol.17
, Issue.9
, pp. 1186-1198
-
-
Yoon, H.1
Yang, K.2
Shahabi, C.3
-
41
-
-
84894681418
-
Distributed human action recognition via wearable motion sensor networks
-
A. Yang, A. Giani, R. Giannatonio, K. Gilani, Distributed Human Action Recognition via Wearable Motion Sensor Networks, Journal of Ambient Intelligence and Smart Environments, 2009.
-
(2009)
Journal of Ambient Intelligence and Smart Environments
-
-
Yang, A.1
Giani, A.2
Giannatonio, R.3
Gilani, K.4
-
42
-
-
34548591821
-
Integrating hidden markov models and spectral analysis for sensory time series clustering
-
J. Yin and Q. Yang, Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering, ICDM, 2005.
-
(2005)
ICDM
-
-
Yin, J.1
Yang, Q.2
-
44
-
-
84879491205
-
USC-HAD: A daily activity dataset for ubiquitous activity recognition using wearable sensors
-
M. Zhang and A.A. Sawchuk, USC-HAD: A Daily Activity Dataset for Ubiquitous Activity Recognition Using Wearable Sensors, Ubi Comp, 2012.
-
(2012)
Ubi Comp
-
-
Zhang, M.1
Sawchuk, A.A.2
-
46
-
-
84894657139
-
-
Project webpage
-
Project webpage: sites.google.com/site/mtdtsadc/
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