An Evolutionary Multiobjective Approach to Sparse Reconstruction
暂无分享,去创建一个
Xin Yao | Maoguo Gong | Lin Li | Shan He | Rustam Stolkin | X. Yao | R. Stolkin | Shan He | Maoguo Gong | Lin Li
[1] J. D. Schaffer,et al. Real-Coded Genetic Algorithms and Interval-Schemata , 1992, FOGA.
[2] L. J. Eshelman,et al. chapter Real-Coded Genetic Algorithms and Interval-Schemata , 1993 .
[3] Zhifeng Zhang,et al. Adaptive Nonlinear Approximations , 1994 .
[4] Amara Lynn Graps,et al. An introduction to wavelets , 1995 .
[5] S. Mallat,et al. Adaptive greedy approximations , 1997 .
[6] A. Neubauer,et al. A theoretical analysis of the non-uniform mutation operator for the modified genetic algorithm , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).
[7] Vladimir N. Temlyakov,et al. The best m-term approximation and greedy algorithms , 1998, Adv. Comput. Math..
[8] Michael A. Saunders,et al. Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..
[9] Indraneel Das. On characterizing the “knee” of the Pareto curve based on Normal-Boundary Intersection , 1999 .
[10] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[11] U. Aickelin,et al. The Application of Bayesian Optimization and Classifier Systems in Nurse Scheduling , 2004, PPSN.
[12] Xin Yao,et al. Digital filter design using multiple pareto fronts , 2004, Soft Comput..
[13] Kalyanmoy Deb,et al. Finding Knees in Multi-objective Optimization , 2004, PPSN.
[14] Kim-Fung Man,et al. Multi-objective hierarchical genetic algorithm for interpretable fuzzy rule-based knowledge extraction , 2005, Fuzzy Sets Syst..
[15] Dmitry M. Malioutov,et al. Homotopy continuation for sparse signal representation , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[16] Kalyanmoy Deb,et al. Improved Pruning of Non-Dominated Solutions Based on Crowding Distance for Bi-Objective Optimization Problems , 2006, 2006 IEEE International Conference on Evolutionary Computation.
[17] Yaochu Jin,et al. Multi-Objective Machine Learning , 2006, Studies in Computational Intelligence.
[18] Yong Wang,et al. A Multiobjective Optimization-Based Evolutionary Algorithm for Constrained Optimization , 2006, IEEE Transactions on Evolutionary Computation.
[19] Xin Yao,et al. Evolving hybrid ensembles of learning machines for better generalisation , 2006, Neurocomputing.
[20] Joel A. Tropp,et al. Sparse Approximation Via Iterative Thresholding , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.
[21] Rajat Raina,et al. Efficient sparse coding algorithms , 2006, NIPS.
[22] Mário A. T. Figueiredo,et al. Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems , 2007, IEEE Journal of Selected Topics in Signal Processing.
[23] Rayan Saab,et al. Sparco: A Testing Framework for Sparse Reconstruction , 2007 .
[24] Qingfu Zhang,et al. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.
[25] Yaochu Jin,et al. Single/Multi-objective Inverse Robust Evolutionary Design Methodology in the Presence of Uncertainty , 2007, Evolutionary Computation in Dynamic and Uncertain Environments.
[26] Lawrence Carin,et al. Bayesian Compressive Sensing , 2008, IEEE Transactions on Signal Processing.
[27] Bernhard Sendhoff,et al. Pareto-Based Multiobjective Machine Learning: An Overview and Case Studies , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[28] Yaakov Tsaig,et al. Fast Solution of $\ell _{1}$ -Norm Minimization Problems When the Solution May Be Sparse , 2008, IEEE Transactions on Information Theory.
[29] Mike E. Davies,et al. Iterative Hard Thresholding for Compressed Sensing , 2008, ArXiv.
[30] E. Candès. The restricted isometry property and its implications for compressed sensing , 2008 .
[31] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[32] E. Candès,et al. Near-ideal model selection by ℓ1 minimization , 2008, 0801.0345.
[33] Stephen J. Wright,et al. Sparse Reconstruction by Separable Approximation , 2008, IEEE Transactions on Signal Processing.
[34] Lily Rachmawati,et al. Multiobjective Evolutionary Algorithm With Controllable Focus on the Knees of the Pareto Front , 2009, IEEE Transactions on Evolutionary Computation.
[35] Allen Y. Yang,et al. Fast ℓ1-minimization algorithms and an application in robust face recognition: A review , 2010, 2010 IEEE International Conference on Image Processing.
[36] Maoguo Gong,et al. ADAPTIVE RANKS CLONE AND k‐NEAREST NEIGHBOR LIST–BASED IMMUNE MULTI‐OBJECTIVE OPTIMIZATION , 2010, Comput. Intell..
[37] Mike E. Davies,et al. Normalized Iterative Hard Thresholding: Guaranteed Stability and Performance , 2010, IEEE Journal of Selected Topics in Signal Processing.
[38] Huanhuan Chen,et al. Multiobjective Neural Network Ensembles Based on Regularized Negative Correlation Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[39] Xin Yao,et al. Multi-Objective Approaches to Optimal Testing Resource Allocation in Modular Software Systems , 2010, IEEE Transactions on Reliability.
[40] Fang Liu,et al. Compressive Sensing SAR Image Reconstruction Based on Bayesian Framework and Evolutionary Computation , 2011, IEEE Transactions on Image Processing.
[41] Junfeng Yang,et al. Alternating Direction Algorithms for 1-Problems in Compressive Sensing , 2009, SIAM J. Sci. Comput..
[42] Xin Yao,et al. Software Module Clustering as a Multi-Objective Search Problem , 2011, IEEE Transactions on Software Engineering.
[43] K. Deb,et al. Understanding knee points in bicriteria problems and their implications as preferred solution principles , 2011 .
[44] Zongben Xu,et al. $L_{1/2}$ Regularization: A Thresholding Representation Theory and a Fast Solver , 2012, IEEE Transactions on Neural Networks and Learning Systems.
[45] Fang Liu,et al. A novel selection evolutionary strategy for constrained optimization , 2013, Inf. Sci..
[46] S. Frick,et al. Compressed Sensing , 2014, Computer Vision, A Reference Guide.