Uncovering delayed patterns in noisy and irregularly sampled time series: An astronomy application
暂无分享,去创建一个
Peter Tiño | Markus Harva | Xin Yao | Juan C. Cuevas-Tello | Somak Raychaudhury | X. Yao | P. Tiňo | M. Harva | Somak Raychaudhury | J. Cuevas-Tello
[1] Nello Cristianini,et al. Kernel Methods for Pattern Analysis , 2003, ICTAI.
[2] Deborah B. Haarsma,et al. The Radio Wavelength Time Delay of Gravitational Lens 0957+561 , 1999 .
[3] Hans-Georg Beyer,et al. A general noise model and its effects on evolution strategy performance , 2006, IEEE Transactions on Evolutionary Computation.
[4] William H. Press,et al. The Time Delay of Gravitational Lens 0957+561. I. Methodology and Analysis of Optical Photometric Data , 1992 .
[5] Jürgen Branke,et al. Evolutionary optimization in uncertain environments-a survey , 2005, IEEE Transactions on Evolutionary Computation.
[6] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[7] M. Oguri. Gravitational Lens Time Delays: A Statistical Assessment of Lens Model Dependences and Implications for the Global Hubble Constant , 2006, astro-ph/0609694.
[8] Peter Tiño,et al. How accurate are the time delay estimates in gravitational lensing? , 2006, ArXiv.
[9] J. Pelt,et al. The light curve and the time delay of QSO 0957+561. , 1995, astro-ph/9501036.
[10] Per Kristian Lehre,et al. On the Effect of Populations in Evolutionary Multi-Objective Optimisation , 2006, Evolutionary Computation.
[11] B. Pindor. Discovering Gravitational Lenses through Measurements of Their Time Delays , 2005, astro-ph/0501518.
[12] Christine A. Shoemaker,et al. Local function approximation in evolutionary algorithms for the optimization of costly functions , 2004, IEEE Transactions on Evolutionary Computation.
[13] Carlos M. Fonseca,et al. GENETIC ALGORITHM TOOLS FOR CONTROL SYSTEMS ENGINEERING , 1994 .
[14] Pierre Magain,et al. COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses. VII. Time delays and the Hubble con , 2008, 0803.4015.
[15] D. A. Preece,et al. An introduction to the statistical analysis of data , 1979 .
[16] J. Wambsganss,et al. The Rewards of Patience: An 822 Day Time Delay in the Gravitational Lens SDSS J1004+4112 , 2007, 0710.1634.
[17] W. Press,et al. The time delay of gravitational lens 0957+561. II: Analysis of radio data and combined optical-radio analysis , 1992 .
[18] D. Walsh,et al. 0957 + 561 A, B: twin quasistellar objects or gravitational lens? , 1979, Nature.
[19] Goldberg,et al. Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.
[20] D. Ruppert. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .
[21] E. Ziegel. Modern Mathematical Statistics , 1989 .
[22] M. Bartelmann. Gravitational lensing , 2010, 1010.3829.
[23] Robert H. Halstead,et al. Matrix Computations , 2011, Encyclopedia of Parallel Computing.
[24] School of Physics,et al. COSMOGRAIL: The COSmological MOnitoring of GRAvItational Lenses - I. How to sample the light curves of gravitationally lensed quasars to measure accurate time delays , 2005 .
[25] F. A. Seiler,et al. Numerical Recipes in C: The Art of Scientific Computing , 1989 .
[26] O. Wucknitz. Gravitational Lensing , 2007, Large-Scale Peculiar Motions.
[27] J. Pelt,et al. Time delay controversy on QSO 0957+561 not yet decided , 1994 .
[28] Peter Tiño,et al. A Kernel-Based Approach to Estimating Phase Shifts Between Irregularly Sampled Time Series: An Application to Gravitational Lenses , 2006, ECML.
[29] D. E. Goldberg,et al. Genetic Algorithms in Search , 1989 .
[30] Markus Harva,et al. Bayesian Estimation of Time Delays Between Unevenly Sampled Signals , 2008, 2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing.
[31] F. Pijpers. The determination of time delays as an inverse problem - the case of the double quasar 0957+561 , 1997 .
[32] P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .
[33] D. Long,et al. A Robust Determination of the Time Delay in 0957+561A, B and a Measurement of the Global Value of Hubble's Constant , 1996, astro-ph/9610162.
[34] P. Magain,et al. A novel approach for extracting time-delays from lightcurves of lensed quasar images , 2001, astro-ph/0110668.
[35] Pat Langley,et al. Learning Process Models with Missing Data , 2006, ECML.
[36] S. Refsdal,et al. On the Possibility of Determining the Distances and Masses of Stars from the Gravitational Lens Effect , 1966 .
[37] Boonserm Kijsirikul,et al. Evolutionary strategies for multi-scale radial basis function kernels in support vector machines , 2005, GECCO '05.
[38] G. Meylan,et al. COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses , 2004, Proceedings of the International Astronomical Union.
[39] Xin Yao,et al. Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..
[40] P. Schechter. The Hubble Constant from Gravitational Lens Time Delays , 2004, Proceedings of the International Astronomical Union.
[41] Jürgen Branke,et al. Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation , 2006, IEEE Transactions on Evolutionary Computation.
[42] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[43] Jonathan E. Rowe,et al. An Evolution Strategy Using a Continuous Version of the Gray-Code Neighbourhood Distribution , 2004, GECCO.
[44] J. Hjorth,et al. ESTIMATION OF MULTIPLE TIME DELAYS IN COMPLEX GRAVITATIONAL LENS SYSTEMS , 1998 .
[45] Ki Won Lee,et al. Around-the-Clock Observations of the Q0957+561A,B Gravitationally Lensed Quasar. II. Results for the Second Observing Season , 2003 .
[46] Yong Lu,et al. A robust stochastic genetic algorithm (StGA) for global numerical optimization , 2004, IEEE Transactions on Evolutionary Computation.
[47] J. Ovaldsen,et al. New aperture photometry of QSO 0957+561; application to time delay and microlensing , 2003, astro-ph/0308397.
[48] Thomas Bäck,et al. Evolutionary Algorithms: The Role of Mutation and Recombination , 2000 .
[49] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[50] Michael G. Madden,et al. The Genetic Kernel Support Vector Machine: Description and Evaluation , 2005, Artificial Intelligence Review.
[51] Volker Nissen,et al. Evolutionary Algorithms in Management Applications , 1995 .
[52] Jin-Kao Hao,et al. A Hybrid GA/SVM Approach for Gene Selection and Classification of Microarray Data , 2006, EvoWorkshops.
[53] W. Jason Owen,et al. Statistical Data Analysis , 2000, Technometrics.
[54] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[55] Neta A. Bahcall,et al. THE SLOAN DIGITAL SKY SURVEY QUASAR LENS SEARCH. II. STATISTICAL LENS SAMPLE FROM THE THIRD DATA RELEASE , 2007, 0708.0828.
[56] David E. Goldberg,et al. Efficient Parallel Genetic Algorithms: Theory and Practice , 2000 .