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pro vyhledávání: '"Gratton S."'
An algorithm for unconstrained non-convex optimization is described, which does not evaluate the objective function and in which minimization is carried out, at each iteration, within a randomly selected subspace. It is shown that this random approxi
Externí odkaz:
http://arxiv.org/abs/2310.16580
A class of multi-level algorithms for unconstrained nonlinear optimization is presented which does not require the evaluation of the objective function. The class contains the momentum-less AdaGrad method as a particular (single-level) instance. The
Externí odkaz:
http://arxiv.org/abs/2302.07049
An adaptive regularization algorithm for unconstrained nonconvex optimization is presented in which the objective function is never evaluated, but only derivatives are used. This algorithm belongs to the class of adaptive regularization methods, for
Externí odkaz:
http://arxiv.org/abs/2203.09947
Autor:
Gratton, S., Toint, Ph. L.
Publikováno v:
Computational Optimization and Applications, 84, pages 573 - 607, 2023
An Adagrad-inspired class of algorithms for smooth unconstrained optimization is presented in which the objective function is never evaluated and yet the gradient norms decrease at least as fast as $\calO(1/\sqrt{k+1})$ while second-order optimality
Externí odkaz:
http://arxiv.org/abs/2203.03351
A class of algorithms for unconstrained nonconvex optimization is considered where the value of the objective function is never computed. The class contains a deterministic version of the first-order Adagrad method typically used for minimization of
Externí odkaz:
http://arxiv.org/abs/2203.01757
A parametric class of trust-region algorithms for unconstrained nonconvex optimization is considered where the value of the objective function is never computed. The class contains a deterministic version of the first-order Adagrad method typically u
Externí odkaz:
http://arxiv.org/abs/2203.01647
Autor:
Planck Collaboration, Akrami, Y., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A. J., Barreiro, R. B., Bartolo, N., Basak, S., Benabed, K., Bernard, J. -P., Bersanelli, M., Bielewicz, P., Bond, J. R., Borrill, J., Bouchet, F. R., Burigana, C., Calabrese, E., Carvalho, P., Chiang, H. C., Crill, B. P., Cuttaia, F., de Rosa, A., de Zotti, G., Delabrouille, J., Delouis, J. -M., Di Valentino, E., Diego, J. M., Dupac, X., Dusini, S., Efstathiou, G., Elsner, F., Enßlin, T. A., Eriksen, H. K., Fernandez-Cobos, R., Finelli, F., Fraisse, A. A., Franceschi, E., Frolov, A., Galeotta, S., Ganga, K., Gerbino, M., González-Nuevo, J., Górski, K. M., Gratton, S., Gruppuso, A., Gudmundsson, J. E., Handley, W., Hansen, F. K., Herranz, D., Hivon, E., Hobson, M., Huang, Z., Jones, W. C., Keihänen, E., Keskitalo, R., Kim, J., Kisner, T. S., Krachmalnicoff, N., Kunz, M., Kurki-Suonio, H., Lamarre, J. -M., Lasenby, A., Lattanzi, M., Lawrence, C. R., Jeune, M. Le, Levrier, F., Lilje, P. B., Lindholm, V., López-Caniego, M., Ma, Y. -Z., Macías-Pérez, J. F., Maggio, G., Mandolesi, N., Marcos-Caballero, A., Maris, M., Martin, P. G., Martínez-González, E., Matarrese, S., Mauri, N., McEwen, J. D., Migliaccio, M., Molinari, D., Moneti, A., Montier, L., Morgante, G., Natoli, P., Paoletti, D., Partridge, B., Perrotta, F., Pettorino, V., Piacentini, F., Polenta, G., Puget, J. -L., Rachen, J. P., Reinecke, M., Remazeilles, M., Renzi, A., Rocha, G., Roudier, G., Ruiz-Granados, B., Savelainen, M., Scott, D., Sirri, G., Spencer, L. D., Suur-Uski, A. -S., Tauber, J. A., Tavagnacco, D., Tenti, M., Toffolatti, L., Tomasi, M., Trombetti, T., Valiviita, J., Van Tent, B., Vielva, P., Villa, F., Wehus, I. K., Zacchei, A., Zonca, A.
Publikováno v:
A&A 644, A99 (2020)
We describe an extension of the most recent version of the Planck Catalogue of Compact Sources (PCCS2), produced using a new multi-band Bayesian Extraction and Estimation Package (BeeP). BeeP assumes that the compact sources present in PCCS2 at 857 G
Externí odkaz:
http://arxiv.org/abs/2009.06333
Autor:
Planck Collaboration, Aghanim, N., Akrami, Y., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A. J., Barreiro, R. B., Bartolo, N., Basak, S., Benabed, K., Bernard, J. -P., Bersanelli, M., Bielewicz, P., Bock, J. J., Bond, J. R., Borrill, J., Bouchet, F. R., Boulanger, F., Bucher, M., Burigana, C., Butler, R. C., Calabrese, E., Cardoso, J. -F., Carron, J., Casaponsa, B., Challinor, A., Chiang, H. C., Colombo, L. P. L., Combet, C., Crill, B. P., Cuttaia, F., de Bernardis, P., de Rosa, A., de Zotti, G., Delabrouille, J., Delouis, J. -M., Di Valentino, E., Diego, J. M., Doré, O., Douspis, M., Ducout, A., Dupac, X., Dusini, S., Efstathiou, G., Elsner, F., Enßlin, T. A., Eriksen, H. K., Fantaye, Y., Fernandez-Cobos, R., Finelli, F., Frailis, M., Fraisse, A. A., Franceschi, E., Frolov, A., Galeotta, S., Galli, S., Ganga, K., Génova-Santos, R. T., Gerbino, M., Ghosh, T., Giraud-Héraud, Y., González-Nuevo, J., Górski, K. M., Gratton, S., Gruppuso, A., Gudmundsson, J. E., Hamann, J., Handley, W., Hansen, F. K., Herranz, D., Hivon, E., Huang, Z., Jaffe, A. H., Jones, W. C., Keihänen, E., Keskitalo, R., Kiiveri, K., Kim, J., Kisner, T. S., Krachmalnicoff, N., Kunz, M., Kurki-Suonio, H., Lagache, G., Lamarre, J. -M., Lasenby, A., Lattanzi, M., Lawrence, C. R., Jeune, M. Le, Levrier, F., Lewis, A., Liguori, M., Lilje, P. B., Lilley, M., Lindholm, V., López-Caniego, M., Lubin, P. M., Ma, Y. -Z., Macías-Pérez, J. F., Maggio, G., Maino, D., Mandolesi, N., Mangilli, A., Marcos-Caballero, A., Maris, M., Martin, P. G., Martínez-González, E., Matarrese, S., Mauri, N., McEwen, J. D., Meinhold, P. R., Melchiorri, A., Mennella, A., Migliaccio, M., Millea, M., Miville-Deschênes, M. -A., Molinari, D., Moneti, A., Montier, L., Morgante, G., Moss, A., Natoli, P., Nørgaard-Nielsen, H. U., Pagano, L., Paoletti, D., Partridge, B., Patanchon, G., Peiris, H. V., Perrotta, F., Pettorino, V., Piacentini, F., Polenta, G., Puget, J. -L., Rachen, J. P., Reinecke, M., Remazeilles, M., Renzi, A., Rocha, G., Rosset, C., Roudier, G., Rubiño-Martín, J. A., Ruiz-Granados, B., Salvati, L., Sandri, M., Savelainen, M., Scott, D., Shellard, E. P. S., Sirignano, C., Sirri, G., Spencer, L. D., Sunyaev, R., Suur-Uski, A. -S., Tauber, J. A., Tavagnacco, D., Tenti, M., Toffolatti, L., Tomasi, M., Trombetti, T., Valiviita, J., Van Tent, B., Vielva, P., Villa, F., Vittorio, N., Wandelt, B. D., Wehus, I. K., Zacchei, A., Zonca, A.
Publikováno v:
A&A 641, A5 (2020)
This paper describes the 2018 Planck CMB likelihoods, following a hybrid approach similar to the 2015 one, with different approximations at low and high multipoles, and implementing several methodological and analysis refinements. With more realistic
Externí odkaz:
http://arxiv.org/abs/1907.12875
Autor:
Planck Collaboration, Akrami, Y., Arroja, F., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A. J., Barreiro, R. B., Bartolo, N., Basak, S., Benabed, K., Bernard, J. -P., Bersanelli, M., Bielewicz, P., Bond, J. R., Borrill, J., Bouchet, F. R., Bucher, M., Burigana, C., Butler, R. C., Calabrese, E., Cardoso, J. -F., Casaponsa, B., Challinor, A., Chiang, H. C., Colombo, L. P. L., Combet, C., Crill, B. P., Cuttaia, F., de Bernardis, P., de Rosa, A., de Zotti, G., Delabrouille, J., Delouis, J. -M., Di Valentino, E., Diego, J. M., Doré, O., Douspis, M., Ducout, A., Dupac, X., Dusini, S., Efstathiou, G., Elsner, F., Enßlin, T. A., Eriksen, H. K., Fantaye, Y., Fergusson, J., Fernandez-Cobos, R., Finelli, F., Frailis, M., Fraisse, A. A., Franceschi, E., Frolov, A., Galeotta, S., Ganga, K., Génova-Santos, R. T., Gerbino, M., González-Nuevo, J., Górski, K. M., Gratton, S., Gruppuso, A., Gudmundsson, J. E., Hamann, J., Handley, W., Hansen, F. K., Herranz, D., Hivon, E., Huang, Z., Jaffe, A. H., Jones, W. C., Jung, G., Keihänen, E., Keskitalo, R., Kiiveri, K., Kim, J., Krachmalnicoff, N., Kunz, M., Kurki-Suonio, H., Lamarre, J. -M., Lasenby, A., Lattanzi, M., Lawrence, C. R., Jeune, M. Le, Levrier, F., Lewis, A., Liguori, M., Lilje, P. B., Lindholm, V., López-Caniego, M., Ma, Y. -Z., Macías-Pérez, J. F., Maggio, G., Maino, D., Mandolesi, N., Marcos-Caballero, A., Maris, M., Martin, P. G., Martínez-González, E., Matarrese, S., Mauri, N., McEwen, J. D., Meerburg, P. D., Meinhold, P. R., Melchiorri, A., Mennella, A., Migliaccio, M., Miville-Deschênes, M. -A., Molinari, D., Moneti, A., Montier, L., Morgante, G., Moss, A., Münchmeyer, M., Natoli, P., Oppizzi, F., Pagano, L., Paoletti, D., Partridge, B., Patanchon, G., Perrotta, F., Pettorino, V., Piacentini, F., Polenta, G., Puget, J. -L., Rachen, J. P., Racine, B., Reinecke, M., Remazeilles, M., Renzi, A., Rocha, G., Rubiño-Martín, J. A., Ruiz-Granados, B., Salvati, L., Savelainen, M., Scott, D., Shellard, E. P. S., Shiraishi, M., Sirignano, C., Sirri, G., Smith, K., Spencer, L. D., Stanco, L., Sunyaev, R., Suur-Uski, A. -S., Tauber, J. A., Tavagnacco, D., Tenti, M., Toffolatti, L., Tomasi, M., Trombetti, T., Valiviita, J., Van Tent, B., Vielva, P., Villa, F., Vittorio, N., Wandelt, B. D., Wehus, I. K., Zacchei, A., Zonca, A.
We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and modal b
Externí odkaz:
http://arxiv.org/abs/1905.05697
An adaptive regularization algorithm using inexact function and derivatives evaluations is proposed for the solution of composite nonsmooth nonconvex optimization. It is shown that this algorithm needs at most $O(|\log(\epsilon)|\,\epsilon^{-2})$ eva
Externí odkaz:
http://arxiv.org/abs/1902.10406