e-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem
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[1] Lothar Thiele,et al. Modular design space exploration framework for embedded systems , 2005 .
[2] Vittorio Zaccaria,et al. ReSPIR: A Response Surface-Based Pareto Iterative Refinement for Application-Specific Design Space Exploration , 2009, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.
[3] Alexander J. Smola,et al. Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations , 2012, ICML.
[4] Marco Laumanns,et al. Bayesian Optimization Algorithms for Multi-objective Optimization , 2002, PPSN.
[5] Andreas Krause,et al. Contextual Gaussian Process Bandit Optimization , 2011, NIPS.
[6] Roberto Battiti,et al. Active Learning of Pareto Fronts , 2014, IEEE Transactions on Neural Networks and Learning Systems.
[7] Michèle Sebag,et al. Collaborative hyperparameter tuning , 2013, ICML.
[8] Chaitali Chakrabarti,et al. Accurate models for estimating area and power of FPGA implementations , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[9] Donald R. Jones,et al. Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..
[10] Joshua D. Knowles,et al. ParEGO: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems , 2006, IEEE Transactions on Evolutionary Computation.
[11] Michael T. M. Emmerich,et al. Single- and multiobjective evolutionary optimization assisted by Gaussian random field metamodels , 2006, IEEE Transactions on Evolutionary Computation.
[12] Burr Settles,et al. Active Learning Literature Survey , 2009 .
[13] Andreas Krause,et al. Active Learning for Multi-Objective Optimization , 2013, ICML.
[14] Jasper Snoek,et al. Bayesian Optimization with Unknown Constraints , 2014, UAI.
[15] Adam D. Bull,et al. Convergence Rates of Efficient Global Optimization Algorithms , 2011, J. Mach. Learn. Res..
[16] Gunter Saake,et al. Predicting performance via automated feature-interaction detection , 2012, 2012 34th International Conference on Software Engineering (ICSE).
[17] Nando de Freitas,et al. A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning , 2010, ArXiv.
[18] E. Vázquez,et al. Convergence properties of the expected improvement algorithm with fixed mean and covariance functions , 2007, 0712.3744.
[19] Markus Püschel,et al. Computer generation of streaming sorting networks , 2012, DAC Design Automation Conference 2012.
[20] D. Dennis,et al. SDO : A Statistical Method for Global Optimization , 1997 .
[21] Shimon Whiteson,et al. A Survey of Multi-Objective Sequential Decision-Making , 2013, J. Artif. Intell. Res..
[22] Kate Smith-Miles,et al. Efficient Identification of the Pareto Optimal Set , 2014, LION.
[23] Qingfu Zhang,et al. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.
[24] Edwin V. Bonilla,et al. Multi-task Gaussian Process Prediction , 2007, NIPS.
[25] Marco Laumanns,et al. SPEA2: Improving the Strength Pareto Evolutionary Algorithm For Multiobjective Optimization , 2002 .
[26] Andreas Krause,et al. Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting , 2009, IEEE Transactions on Information Theory.
[27] Gary B. Lamont,et al. Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation) , 2006 .
[28] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[29] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[30] Jasper Snoek,et al. Multi-Task Bayesian Optimization , 2013, NIPS.
[31] Oscar Almer,et al. A Learning-Based Approach to the Automated Design of MPSoC Networks , 2011, ARCS.
[32] Qingfu Zhang,et al. Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model , 2010, IEEE Transactions on Evolutionary Computation.
[33] Andreas Krause,et al. "Smart" design space sampling to predict Pareto-optimal solutions , 2012, LCTES '12.
[34] Petros Koumoutsakos,et al. Accelerating evolutionary algorithms with Gaussian process fitness function models , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).