Machine-assisted discovery of relationships in astronomy
暂无分享,去创建一个
Ciro Donalek | Ashish A. Mahabal | Matthew J. Graham | Andrew J. Drake | S. G. Djorgovski | S. Djorgovski | A. Mahabal | A. Drake | M. Graham | C. Donalek
[1] S. Djorgovski,et al. Flashes in a star stream: Automated classification of astronomical transient events , 2012, 2012 IEEE 8th International Conference on E-Science.
[2] C. Bailer-Jones,et al. The expected performance of stellar parametrization with Gaia spectrophotometry , 2012, 1207.6005.
[3] Ashok N. Srivastava,et al. Advances in Machine Learning and Data Mining for Astronomy , 2012 .
[4] T. Speed. A Correlation for the 21st Century , 2011, Science.
[5] Michael Mitzenmacher,et al. Detecting Novel Associations in Large Data Sets , 2011, Science.
[6] Andrew McWilliam,et al. RR Lyrae Stars, Metal-Poor Stars, and the Galaxy , 2011, 1109.1324.
[7] Christopher N. Beaumont,et al. CLASSIFYING STRUCTURES IN THE INTERSTELLAR MEDIUM WITH SUPPORT VECTOR MACHINES: THE G16.05-0.57 SUPERNOVA REMNANT , 2011, 1107.5584.
[8] M. Catelán,et al. RR Lyrae Period-Amplitude Diagrams: From Bailey to Today , 2011, 1106.4809.
[9] B. Sesar. Mapping the Galactic Halo with SDSS, LINEAR and PTF RR Lyrae Stars , 2011, 1105.4146.
[10] Joshua S. Bloom,et al. Data Mining and Machine-Learning in Time-Domain Discovery & Classification , 2011, 1104.3142.
[11] R. Ibata,et al. AAOmega spectroscopy of 29 351 stars in fields centered on ten Galactic globular clusters , 2011, 1104.2628.
[12] P. Dubath,et al. Random forest automated supervised classification of Hipparcos periodic variable stars , 2011, 1101.2406.
[13] J. Richards,et al. ON MACHINE-LEARNED CLASSIFICATION OF VARIABLE STARS WITH SPARSE AND NOISY TIME-SERIES DATA , 2011, 1101.1959.
[14] E. C. Vasconcellos,et al. DECISION TREE CLASSIFIERS FOR STAR/GALAXY SEPARATION , 2010, 1011.1951.
[15] Nathaniel R. Butler,et al. OPTIMAL TIME-SERIES SELECTION OF QUASARS , 2010, 1008.3143.
[16] N. S. Philip,et al. Results from the Supernova Photometric Classification Challenge , 2010, 1008.1024.
[17] J. Eisert,et al. Extracting dynamical equations from experimental data is NP hard. , 2010, Physical review letters.
[18] Maria Liakata,et al. Towards Robot Scientists for autonomous scientific discovery , 2010, Automated experimentation.
[19] Jayanta Dutta,et al. SEARCH FOR CHAOS IN NEUTRON STAR SYSTEMS: IS Cyg X-3 A BLACK HOLE? , 2009, 0911.1701.
[20] P. Stetson,et al. A NEW COLOR–MAGNITUDE DIAGRAM FOR 47 TUCANAE: A STATISTICAL ANALYSIS , 2009 .
[21] B. Skiff,et al. VizieR Online Data Catalog , 2009 .
[22] Canada.,et al. Data Mining and Machine Learning in Astronomy , 2009, 0906.2173.
[23] Hod Lipson,et al. Distilling Free-Form Natural Laws from Experimental Data , 2009, Science.
[24] Heidi Jo Newberg,et al. SEGUE: A SPECTROSCOPIC SURVEY OF 240,000 STARS WITH g = 14–20 , 2009, 0902.1781.
[25] L. Zaninetti. SEMI-ANALYTICAL FORMULAS FOR THE HERTZSPRUNG-RUSSELL DIAGRAM , 2008, 0811.4524.
[26] A. J. Drake,et al. FIRST RESULTS FROM THE CATALINA REAL-TIME TRANSIENT SURVEY , 2008, 0809.1394.
[27] B. Gibson,et al. THE RADIAL VELOCITY EXPERIMENT (RAVE): SECOND DATA RELEASE , 2008, 0806.0546.
[28] Mamoru Doi,et al. The Milky Way Tomography with SDSS. II. Stellar Metallicity , 2008, 0804.3850.
[29] L. M. Sarro,et al. Automated supervised classification of variable stars - I. Methodology , 2007, 0711.0703.
[30] M. Montuori,et al. Basic properties of galaxy clustering in the light of recent results from the Sloan Digital Sky Survey , 2005, astro-ph/0501583.
[31] Christopher H. Bryant,et al. Functional genomic hypothesis generation and experimentation by a robot scientist , 2004, Nature.
[32] J. Hurley,et al. Impersonal parameters from Hertzsprung-Russell diagrams , 2003 .
[33] Foster J. Provost,et al. Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction , 2003, J. Artif. Intell. Res..
[34] Brian D. Warner,et al. The Society for Astronomical Sciences 21st Annual Symposium on Telescope Science , 2002 .
[35] F. Ochsenbein,et al. The VizieR database of astronomical catalogues , 2000, astro-ph/0002122.
[36] J. Lucey,et al. The fundamental relations of elliptical galaxies , 1993 .
[37] Frederic H. Chaffee,et al. An objective classification scheme for QSO spectra , 1992 .
[38] R. Davies,et al. Spectroscopy and photometry of elliptical galaxies. I: a new distance estimator , 1987 .
[39] S. Djorgovski,et al. Fundamental Properties of Elliptical Galaxies , 1987 .
[40] J. Scargle. Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data , 1982 .
[41] N. Lomb. Least-squares frequency analysis of unequally spaced data , 1976 .
[42] Lior Rokach,et al. Data Mining And Knowledge Discovery Handbook , 2005 .
[43] Teuvo Kohonen,et al. Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.
[44] John R. Koza,et al. Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.
[45] Thomas M. Cover,et al. The Best Two Independent Measurements Are Not the Two Best , 1974, IEEE Trans. Syst. Man Cybern..