-
1
-
-
35048842427
-
Activity recognition from userannotated acceleration data
-
ser. Lecture Notes in Computer Science 3001. Springer
-
L. Bao and S. S. Intille, "Activity recognition from userannotated acceleration data." in Pervasive Computing, ser. Lecture Notes in Computer Science 3001. Springer, 2004, pp. 1-17.
-
(2004)
Pervasive Computing
, pp. 1-17
-
-
Bao, L.1
Intille, S.S.2
-
2
-
-
30744462795
-
Activity classification using realistic data from wearable sensors
-
J. Präkkä, M. Ermes, P. Korpipää, J. Mäntyjärvi, J. Peltola, and I. Korhonen, "Activity classification using realistic data from wearable sensors." IEEE Transactions on Information Technology in Biomedicine, vol. 10, no. 1, pp. 119-128, 2006.
-
(2006)
IEEE Transactions on Information Technology in Biomedicine
, vol.10
, Issue.1
, pp. 119-128
-
-
Präkkä, J.1
Ermes, M.2
Korpipää, P.3
Mäntyjärvi, J.4
Peltola, J.5
Korhonen, I.6
-
3
-
-
29344474528
-
Activity recognition from accelerometer data
-
N. Ravi, N. Dandekar, P. Mysore, and M. L. Littman, "Activity recognition from accelerometer data." in Proceedings of AAAI'05, 2005, pp. 1541-1546.
-
(2005)
Proceedings of AAAI'05
, pp. 1541-1546
-
-
Ravi, N.1
Dandekar, N.2
Mysore, P.3
Littman, M.L.4
-
4
-
-
79957944589
-
Large scale real-life action recognition using conditional random fields with stochastic training
-
ser. Lecture Notes in Computer Science, J. Z. Huang, L. Cao, and J. Srivastava, Eds. Springer
-
X. Sun, H. Kashima, R. Tomioka, and N. Ueda, "Large scale real-life action recognition using conditional random fields with stochastic training." in PAKDD (2011), ser. Lecture Notes in Computer Science, J. Z. Huang, L. Cao, and J. Srivastava, Eds., vol. 6635. Springer, 2011, pp. 222-233.
-
(2011)
PAKDD (2011)
, vol.6635
, pp. 222-233
-
-
Sun, X.1
Kashima, H.2
Tomioka, R.3
Ueda, N.4
-
5
-
-
59249093678
-
Discovery of activity patterns using topic models
-
ACM
-
T. Huynh, M. Fritz, and B. Schiele, "Discovery of activity patterns using topic models," in Proceedings of the 10th international conference on Ubiquitous computing. ACM, 2008, pp. 10-19.
-
(2008)
Proceedings of the 10th International Conference on Ubiquitous Computing
, pp. 10-19
-
-
Huynh, T.1
Fritz, M.2
Schiele, B.3
-
6
-
-
79951744105
-
Averaged stochastic gradient descent with feedback: An accurate, robust, and fast training method
-
X. Sun, H. Kashima, T. Matsuzaki, and N. Ueda, "Averaged stochastic gradient descent with feedback: An accurate, robust, and fast training method." in Proceedings of the 10th International Conference on Data Mining (ICDM'10), 2010, pp. 1067-1072.
-
(2010)
Proceedings of the 10th International Conference on Data Mining (ICDM'10)
, pp. 1067-1072
-
-
Sun, X.1
Kashima, H.2
Matsuzaki, T.3
Ueda, N.4
-
7
-
-
0142192295
-
Conditional random fields: Probabilistic models for segmenting and labeling sequence data
-
J. Lafferty, A. McCallum, and F. Pereira, "Conditional random fields: Probabilistic models for segmenting and labeling sequence data," in Proceedings of the 18th International Conference on Machine Learning (ICML'01), 2001, pp. 282-289.
-
(2001)
Proceedings of the 18th International Conference on Machine Learning (ICML'01)
, pp. 282-289
-
-
Lafferty, J.1
McCallum, A.2
Pereira, F.3
-
8
-
-
0013309537
-
Online algorithms and stochastic approximations
-
Saad, David. Cambridge University Press
-
L. Bottou, "Online algorithms and stochastic approximations," Online Learning and Neural Networks. Saad, David. Cambridge University Press, 1998.
-
(1998)
Online Learning and Neural Networks
-
-
Bottou, L.1
-
9
-
-
55149088329
-
Convex multi-task feature learning
-
A. Argyriou, T. Evgeniou, and M. Pontil, "Convex multi-task feature learning." Machine Learning, vol. 73, no. 3, pp. 243-272, 2008.
-
(2008)
Machine Learning
, vol.73
, Issue.3
, pp. 243-272
-
-
Argyriou, A.1
Evgeniou, T.2
Pontil, M.3
-
10
-
-
34547974802
-
The matrix stick-breaking process for flexible multi-task learning
-
Corvalis, Oregon: ACM
-
Y. Xue, D. Dunson, and L. Carin, "The matrix stick-breaking process for flexible multi-task learning," in Proceedings of the 24th international conference on Machine learning (ICML'07). Corvalis, Oregon: ACM, 2007, pp. 1063-1070.
-
(2007)
Proceedings of the 24th International Conference on Machine Learning (ICML'07)
, pp. 1063-1070
-
-
Xue, Y.1
Dunson, D.2
Carin, L.3
-
11
-
-
78049387979
-
Matrix regularization techniques for online multitask learning
-
Oct
-
A. Agarwal, A. Rakhlin, and P. Bartlett, "Matrix regularization techniques for online multitask learning," EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2008-138, Oct 2008.
-
(2008)
EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2008-138
-
-
Agarwal, A.1
Rakhlin, A.2
Bartlett, P.3
-
12
-
-
78651304213
-
Online learning for multitask feature selection
-
ACM
-
H. Yang, I. King, and M. R. Lyu, "Online learning for multitask feature selection." in Proceedings of CIKM'10. ACM, 2010, pp. 1693-1696.
-
(2010)
Proceedings of CIKM'10
, pp. 1693-1696
-
-
Yang, H.1
King, I.2
Lyu, M.R.3
-
13
-
-
79951751763
-
Operation and baseline assessment of large scale activity gathering system by mobile device
-
Y. Hattori, M. Takemori, S. Inoue, G. Hirakawa, and O. Sudo, "Operation and baseline assessment of large scale activity gathering system by mobile device," in Proceedings of DICOMO' 10, 2010.
-
(2010)
Proceedings of DICOMO'10
-
-
Hattori, Y.1
Takemori, M.2
Inoue, S.3
Hirakawa, G.4
Sudo, O.5
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