-
3
-
-
77956526263
-
Surrogating the surrogate: Accelerating Gaussian-process-based global optimization with a mixture cross-entropy algorithm
-
Bardenet, R. and Kégl, B. Surrogating the surrogate: accelerating Gaussian-process-based global optimization with a mixture cross-entropy algorithm. In International Conference on Machine Learning, pp. 55-62, 2010.
-
(2010)
International Conference on Machine Learning
, pp. 55-62
-
-
Bardenet, R.1
Kégl, B.2
-
4
-
-
85162384813
-
Algorithms for hyper-parameter optimization
-
Bergstra, J., Bardenet, R., Bengio, Y., and Kégl, B. Algorithms for hyper-parameter optimization. In Advances in Neural Information Processing Systems, pp. 2546-2554, 2011.
-
(2011)
Advances in Neural Information Processing Systems
, pp. 2546-2554
-
-
Bergstra, J.1
Bardenet, R.2
Bengio, Y.3
Kégl, B.4
-
5
-
-
85161994270
-
Active preference learning with discrete choice data
-
Brochu, E., de Freitas, N., and Ghosh, A. Active preference learning with discrete choice data. In Advances in Neural Information Processing Systems, pp. 409-416, 2007.
-
(2007)
Advances in Neural Information Processing Systems
, pp. 409-416
-
-
Brochu, E.1
De Freitas, N.2
Ghosh, A.3
-
6
-
-
77958068642
-
-
Technical Report UBC TR-2009-23 and arXiv:1012.2599v1, Dept. of Computer Science, University of British Columbia
-
Brochu, E., and Cora, V. M., and de Freitas, N. A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning. Technical Report UBC TR-2009-23 and arXiv:1012.2599v1, Dept. of Computer Science, University of British Columbia, 2009.
-
(2009)
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
-
-
Brochu, E.1
Cora, V.M.2
De Freitas, N.3
-
7
-
-
85010477658
-
A Bayesian interactive optimization approach to procedural animation design
-
Brochu, E., Brochu, T., and de Freitas, N. A Bayesian interactive optimization approach to procedural animation design. In Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 103-112, 2010.
-
(2010)
Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
, pp. 103-112
-
-
Brochu, E.1
Brochu, T.2
De Freitas, N.3
-
8
-
-
79960128338
-
X-armed bandits
-
Bubeck, S., Munos, R., Stoltz, G., and Szepesvari, C. X-armed bandits. Journal of Machine Learning Research, 12:1655-1695, 2011.
-
(2011)
Journal of Machine Learning Research
, vol.12
, pp. 1655-1695
-
-
Bubeck, S.1
Munos, R.2
Stoltz, G.3
Szepesvari, C.4
-
9
-
-
80555140070
-
Convergence rates of efficient global optimization algorithms
-
Bull, A. D. Convergence rates of efficient global optimization algorithms. Journal of Machine Learning Research, 12:2879-2904, 2011.
-
(2011)
Journal of Machine Learning Research
, vol.12
, pp. 2879-2904
-
-
Bull, A.D.1
-
13
-
-
77954515653
-
Bayesian Optimization for sensor set selection
-
ACM
-
Garnett, R., and Osborne, M. A., and Roberts, S. J. Bayesian optimization for sensor set selection. In ACM/IEEE International Conference on Information Processing in Sensor Networks, pp. 209-219. ACM, 2010.
-
(2010)
ACM/IEEE International Conference on Information Processing in Sensor Networks
, pp. 209-219
-
-
Garnett, R.1
Osborne, M.A.2
Roberts, S.J.3
-
14
-
-
33847339319
-
Posterior consistency of Gaussian process prior for nonparametric binary regression
-
Ghosal, S. and Roy, A. Posterior consistency of Gaussian process prior for nonparametric binary regression. The Annals of Statistics, 34:2413-2429, 2006.
-
(2006)
The Annals of Statistics
, vol.34
, pp. 2413-2429
-
-
Ghosal, S.1
Roy, A.2
-
15
-
-
0035377566
-
Completely derandomized self-adaptation in evolution strategies
-
Hansen, N. and Ostermeier, A. Completely derandomized self-adaptation in evolution strategies. Evol. Comput., 9(2):159-195, 2001.
-
(2001)
Evol. Comput.
, vol.9
, Issue.2
, pp. 159-195
-
-
Hansen, N.1
Ostermeier, A.2
-
17
-
-
78751705157
-
New inference strategies for solving Markov decision processes using reversible jump MCMC
-
Hoffman, M., Kueck, H., de Freitas, N., and Doucet, A. New inference strategies for solving Markov decision processes using reversible jump MCMC. In Uncertainty in Artificial Intelligence, pp. 223-231, 2009.
-
(2009)
Uncertainty in Artificial Intelligence
, pp. 223-231
-
-
Hoffman, M.1
Kueck, H.2
De Freitas, N.3
Doucet, A.4
-
18
-
-
80053160717
-
Portfolio allocation for Bayesian optimization
-
Hoffman, M., Brochu, E., and de Freitas, N. Portfolio allocation for Bayesian optimization. In Uncertainty in Artificial Intelligence, pp. 327-336, 2011.
-
(2011)
Uncertainty in Artificial Intelligence
, pp. 327-336
-
-
Hoffman, M.1
Brochu, E.2
De Freitas, N.3
-
19
-
-
84955451375
-
On correlation and budget constraints in model-based multi-armed-bandit optimization with application to automatic machine learning
-
Hoffman, M.W., Shahriari, B., and de Freitas, N. On correlation and budget constraints in model-based multi-armed-bandit optimization with application to automatic machine learning. In AI and Statistics, 2014.
-
(2014)
AI and Statistics
-
-
Hoffman, M.W.1
Shahriari, B.2
De Freitas, N.3
-
20
-
-
84868554032
-
Sequential model-based optimization for general algorithm configuration
-
Hutter, F., and Hoos, H. H., and Leyton-Brown, K. Sequential model-based optimization for general algorithm configuration. In Proceedings of LION-5, pp. 507-523, 2011.
-
(2011)
Proceedings of LION-5
, pp. 507-523
-
-
Hutter, F.1
Hoos, H.H.2
Leyton-Brown, K.3
-
21
-
-
0027678534
-
Lipschitzian optimization without the lipschitz constant
-
Jones, D. R., and Perttunen, C. D., and Stuckman, B. E. Lipschitzian optimization without the Lipschitz constant. Journal of Optimization Theory and Applications, 79(1): 157-181, 1993.
-
(1993)
Journal of Optimization Theory and Applications
, vol.79
, Issue.1
, pp. 157-181
-
-
Jones, D.R.1
Perttunen, C.D.2
Stuckman, B.E.3
-
22
-
-
0035577808
-
A taxonomy of global optimization methods based on response surfaces
-
Jones, D.R. A taxonomy of global optimization methods based on response surfaces. J. of Global Optimization, 21(4):345-383, 2001.
-
(2001)
J. of Global Optimization
, vol.21
, Issue.4
, pp. 345-383
-
-
Jones, D.R.1
-
23
-
-
84867888479
-
Thompson sampling: An asymptotically optimal finite-time analysis
-
Springer Berlin Heidelberg
-
Kaufmann, E., Korda, N., and Munos, R. Thompson sampling: An asymptotically optimal finite-time analysis. In Algorithmic Learning Theory, Volume 7568 of Lecture Notes in Computer Science, pp. 199-213. Springer Berlin Heidelberg, 2012.
-
(2012)
Algorithmic Learning Theory, Volume 7568 of Lecture Notes in Computer Science
, pp. 199-213
-
-
Kaufmann, E.1
Korda, N.2
Munos, R.3
-
24
-
-
4944229711
-
GENIA corpus - A semantically annotated corpus for bio-textmining
-
Kim, J., Ohta, T., Tateisi, Y., and ichi Tsujii, J. GENIA corpus - a semantically annotated corpus for bio-textmining. In ISMB (Supplement of Bioinformatics), pp. 180-182, 2003.
-
(2003)
ISMB (Supplement of Bioinformatics)
, pp. 180-182
-
-
Kim, J.1
Ohta, T.2
Tateisi, Y.3
Ichi Tsujii, J.4
-
26
-
-
48049104852
-
SMC samplers for Bayesian optimal nonlinear design
-
Kueck, H., de Freitas, N., and Doucet, A. SMC samplers for Bayesian optimal nonlinear design. In IEEE Nonlinear Statistical Signal Processing Workshop, pp. 99-102, 2006.
-
(2006)
IEEE Nonlinear Statistical Signal Processing Workshop
, pp. 99-102
-
-
Kueck, H.1
De Freitas, N.2
Doucet, A.3
-
27
-
-
68749108525
-
Inference and learning for active sensing, experimental design and control
-
Araujo, H., Mendonca, A., Pinho, A., and Torres, M. (eds.) Springer Berlin Heidelberg
-
Kueck, H., Hoffman, M., Doucet, A., and de Freitas, N. Inference and learning for active sensing, experimental design and control. In Araujo, H., Mendonca, A., Pinho, A., and Torres, M. (eds.), Pattern Recognition and Image Analysis, Volume 5524, pp. 1-10. Springer Berlin Heidelberg, 2009.
-
(2009)
Pattern Recognition and Image Analysis
, vol.5524
, pp. 1-10
-
-
Kueck, H.1
Hoffman, M.2
Doucet, A.3
De Freitas, N.4
-
28
-
-
84896062990
-
An experimental methodology for response surface optimization methods
-
Lizotte, D., Greiner, R., and Schuurmans, D. An experimental methodology for response surface optimization methods. J. of Global Optimization, pp. 1-38, 2011.
-
(2011)
J. of Global Optimization
, pp. 1-38
-
-
Lizotte, D.1
Greiner, R.2
Schuurmans, D.3
-
29
-
-
84954528329
-
Adaptive MCMC with Bayesian optimization
-
Mahendran, N., Wang, Z., Hamze, F., and de Freitas, N. Adaptive MCMC with Bayesian optimization. Journal of Machine Learning Research - Proceedings Track, 22: 751-760, 2012.
-
(2012)
Journal of Machine Learning Research - Proceedings Track
, vol.22
, pp. 751-760
-
-
Mahendran, N.1
Wang, Z.2
Hamze, F.3
De Freitas, N.4
-
30
-
-
51349157486
-
Active policy learning for robot planning and exploration under uncertainty
-
Martinez-Cantin, R., de Freitas, N., Doucet, A., and Castellanos, J. A. Active policy learning for robot planning and exploration under uncertainty. Robotics Science and Systems, 2007.
-
(2007)
Robotics Science and Systems
-
-
Martinez-Cantin, R.1
De Freitas, N.2
Doucet, A.3
Castellanos, J.A.4
-
31
-
-
84860620509
-
Optimistic Bayesian sampling in contextual bandit problems
-
School of Mathematics, University of Bristol
-
May, B. C., Korda, N., Lee, A., and Leslie, D. S. Optimistic Bayesian sampling in contextual bandit problems. Technical Report 11:01 Statistics Group, School of Mathematics, University of Bristol, 2011.
-
(2011)
Technical Report 11:01 Statistics Group
-
-
May, B.C.1
Korda, N.2
Lee, A.3
Leslie, D.S.4
-
32
-
-
84867137347
-
The Bayesian approach to global optimization
-
Springer
-
Močkus, J. The Bayesian approach to global optimization. In Systems Modeling and Optimization, Volume 38, pp. 473-481. Springer, 1982.
-
(1982)
Systems Modeling and Optimization
, vol.38
, pp. 473-481
-
-
Močkus, J.1
-
33
-
-
85162504694
-
Optimistic optimization of a deterministic function without the knowledge of its smoothness
-
Munos, R. Optimistic optimization of a deterministic function without the knowledge of its smoothness. In Advances in Neural Information Processing Systems, pp. 783-791, 2011.
-
(2011)
Advances in Neural Information Processing Systems
, pp. 783-791
-
-
Munos, R.1
-
34
-
-
84955439192
-
From bandits to Monte-Carlo tree search: The optimistic principle applied to optimization and planning
-
Munos, R. From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning. Technical Report hal-00747575, INRIA Lille, 2014.
-
(2014)
Technical Report Hal-00747575, INRIA Lille
-
-
Munos, R.1
-
35
-
-
82055172940
-
Towards the web of concepts: Extracting concepts from large datasets
-
Parameswaran, A., Garcia-Molina, H., and Rajaraman, A. Towards the web of concepts: Extracting concepts from large datasets. Proceedings of the VLDB Endowment, 3 (1-2):566-577, 2010.
-
(2010)
Proceedings of the VLDB Endowment
, vol.3
, Issue.1-2
, pp. 566-577
-
-
Parameswaran, A.1
Garcia-Molina, H.2
Rajaraman, A.3
-
38
-
-
77956501313
-
Gaussian process optimization in the bandit setting: No regret and experimental design
-
Srinivas, N., Krause, A., Kakade, S. M., and Seeger, M. Gaussian process optimization in the bandit setting: No regret and experimental design. In International Conference on Machine Learning, pp. 1015-1022, 2010.
-
(2010)
International Conference on Machine Learning
, pp. 1015-1022
-
-
Srinivas, N.1
Krause, A.2
Kakade, S.M.3
Seeger, M.4
-
41
-
-
77954033598
-
Convergence properties of the expected improvement algorithm with fixed mean and covariance functions
-
Vazquez, E. and Bect, J. Convergence properties of the expected improvement algorithm with fixed mean and covariance functions. J. of Statistical Planning and Inference, 140:3088-3095, 2010.
-
(2010)
J. of Statistical Planning and Inference
, vol.140
, pp. 3088-3095
-
-
Vazquez, E.1
Bect, J.2
-
42
-
-
84896058897
-
Bayesian optimization in high dimensions via random embeddings
-
Wang, Z., Zoghi, M., Matheson, D., Hutter, F., and de Freitas, N. Bayesian optimization in high dimensions via random embeddings. In International Joint Conference on Artificial Intelligence, 2013.
-
(2013)
International Joint Conference on Artificial Intelligence
-
-
Wang, Z.1
Zoghi, M.2
Matheson, D.3
Hutter, F.4
De Freitas, N.5
|