Sebanyak 11 item atau buku ditemukan

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2010, Athens, Greece, September 5-9, 2011, Proceedings

This volume, the first in a three-volume set, constitutes the refereed proceedings of the European conference on machine learning and knowledge discovery in databases held in Athens, Greece, in September 2011.

Barto, A.G., Sutton, R.S., Anderson, C.: Neuron-like elements that can solve
difficult learning control problems. IEEE Transaction on Systems, Man and
Cybernetics 13, 835–846 (1983) Bhatnagar, S., Sutton, R.S., Ghavamzadeh, M.,
Lee, M.: ...

Machine Learning and Knowledge Discovery in Databases

European Conference, Antwerp, Belgium, September 15-19, 2008, Proceedings

This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.

Sutton, R.S., Barto, A.G.: Introduction to Reinforcement Learning. MIT Press,
Cambridge (1998) 2. Tesauro, G.: TD-Gammon, a self-teaching backgammon
program, achieves masterlevel play. Neural Computation 6(2), 215–219 (1994) 3
.

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings

This two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, UK, in September 2012. The 105 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 443 submissions. The final sections of the proceedings are devoted to Demo and Nectar papers. The Demo track includes 10 papers (from 19 submissions) and the Nectar track includes 4 papers (from 14 submissions). The papers grouped in topical sections on association rules and frequent patterns; Bayesian learning and graphical models; classification; dimensionality reduction, feature selection and extraction; distance-based methods and kernels; ensemble methods; graph and tree mining; large-scale, distributed and parallel mining and learning; multi-relational mining and learning; multi-task learning; natural language processing; online learning and data streams; privacy and security; rankings and recommendations; reinforcement learning and planning; rule mining and subgroup discovery; semi-supervised and transductive learning; sensor data; sequence and string mining; social network mining; spatial and geographical data mining; statistical methods and evaluation; time series and temporal data mining; and transfer learning.

Schaal, S.: Is Imitation Learning the Route to Humanoid Robots? Trends in
Cognitive Sciences 3(6), 233–242 (1999) 2. Abbeel, P., Ng, A.Y.: Apprenticeship
Learning via Inverse Reinforcement Learning. In: Proceedings of the Twenty-first
 ...

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings

This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

21. 22. 23. 24. 2. Abe, N., Mamitsuka, H.: Query learning strategies using
boosting and bagging. In: Proc. of ICML 1998, pp. 1–10 (1998) 3. Donmez, P.,
Carbonell, J.G.: Optimizing estimated loss reduction for active sampling in rank
learning.

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings

This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.

14. 15. 16. 17. 18. 19. Ackley, H., Hinton, E., Sejnowski, J.: A learning algorithm
for boltzmann machines. Cognitive Science, 147–169 (1985) 2. Bengio, Y.:
Learning deep architectures for AI. Foundations and Trends in Machine Learning
2(1), ...

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings

The three volume set LNAI 9851, LNAI 9852, and LNAI 9853 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2016, held in Riva del Garda, Italy, in September 2016. The 123 full papers and 16 short papers presented were carefully reviewed and selected from a total of 460 submissions. The papers presented focus on practical and real-world studies of machine learning, knowledge discovery, data mining; innovative prototype implementations or mature systems that use machine learning techniques and knowledge discovery processes in a real setting; recent advances at the frontier of machine learning and data mining with other disciplines. Part I and Part II of the proceedings contain the full papers of the contributions presented in the scientific track and abstracts of the scientific plenary talks. Part III contains the full papers of the contributions presented in the industrial track, short papers describing demonstration, the nectar papers, and the abstracts of the industrial plenary talks.

18. 19. 20. 21. 22. 23. 24. 25. Mannor, S., Menache, I., Hoze, A., Klein, U.:
Dynamic abstraction in reinforcement learning via clustering. In: Proceedings of
the Twenty-first International Conference on Machine Learning, ICML 2004, pp.
71–78.

Machine Learning and Knowledge Discovery in Databases, Part III

European Conference, ECML PKDD 2010, Athens, Greece, September 5-9, 2011, Proceedings

This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.

Campbell, C., Cristianini, N., Smola, A.J.: Query learning with large margin
classifiers. In: Proceedings of the Seventeenth International Conference on
Machine Learning, pp. 111–118. Stanford University, Standord (2000) 5. Schohn,
G., Cohn ...

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings

The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.

Gu, Q., Li, Z., Han, J.: Joint feature selection and subspace learning. In: IJCAI
Proceedings-International Joint Conference on Artificial Intelligence, vol. 22, p.
1294 (2011) Han, L., Zhang, Y.: Learning multi-level task groups in multi-task
learning ...

Machine Learning and Knowledge Discovery in Databases, Part II

European Conference, ECML PKDD 2010, Athens, Greece, September 5-9, 2011, Proceedings

This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.

It has been shown that transferring knowledge between several potentially
related learning tasks has improved performance. This scenario, termed multi-
task learning [6] or transfer learning [14], has gained considerable attention in the
 ...

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2009, Antwerp, Belgium, September 7-11, 2009 : Proceedings

This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009. The 106 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 422 paper submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.

In the general (non-parameterized) case, or when the prior “decorrelates” the re-
ward in different states, we do not expect active learning to bring a significant
advantage. We are currently conducting further experiments to gain a clearer ...