Results 101 to 110 of about 6,698,594 (332)
Using regression to improve local convergence
2007 IEEE Congress on Evolutionary Computation, 2007 Traditionally Evolutionary Algorithms (EAs) choose candidate solutions based on their individual fitnesses, usually without directly looking for patterns in the fitness landscape discovered. These patterns often contain useful information that could be used to guide the EA to the optimum. While an EA is able to quickly locate the general area of a peak,Stefan Bird, Xiaodong Li 0001openaire +2 more sourcesIntegrating Patient‐Reported Quality Measures in Systemic Lupus Erythematosus: Development of the American College of Rheumatology Implementation Guide
Arthritis Care &Research, EarlyView.Objective
To support high‐quality, patient‐centered care for systemic lupus erythematosus (SLE), the American College of Rheumatology (ACR) developed evidence‐based measures incorporating clinical and patient‐reported outcome measures (PROMs). Using the Consolidated Framework for Implementation Research (CFIR), we conducted semistructured interviews ...Catherine Nasrallah, Cherish Wilson, Christine Hariz, Christie M. Bartels, Shanthini Kasturi, Wambui Machua, Amy Bennett, Kate Chiseri, Allison Plitman, Starla Hairston Blanks, April Jorge, Patti Katz, Jinoos Yazdany, Shivani Garg +13 morewiley +1 more sourceSome Convergence Properties of Broyden's Method [PDF]
In 1965 Broyden introduced a family of algorithms called(rank-one) quasi—New-ton methods for iteratively solving systems of nonlinear equations. We show that when any member of this family is applied to an n x n nonsingular system of linear equations ...David M. Gaycore Cumulative Social Disadvantage and Disease Activity in Juvenile Idiopathic Arthritis: A Childhood Arthritis and Rheumatology Research Alliance Registry Study
Arthritis Care &Research, EarlyView.Objective
Social determinants of health (SDOH) contribute to juvenile idiopathic arthritis (JIA) disparities, but most studies have assessed SDOH independently rather than cumulatively across individual, family, and neighborhood levels. Using a socioecological framework, we investigated the relationship among cumulative social disadvantage ...William Daniel Soulsby, John Boscardin, Andrea Knight, Daniel B. Horton, Karine Toupin‐April, Emily von Scheven, on behalf of the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry Investigators and for the CARRA Health Equity Work Group, R. Aamir, K. Abulaban, A. Adams, C. Aguiar Lapsia, H. Ahmed, S. Akoghlanian, A. AlBijadi, E. Allenspach, M. Alpizar, G. Amarilyo, M. Amoruso, S. Angeles‐Han, S. Ardoin, S. Armendariz, N. Aviran Dagan, I. Balboni, S. Balevic, S. Ballinger, S. Baluta, L. Barillas‐Arias, L. Barillas‐Arias, M. Basiaga, K. Baszis, M. Becker, A. Begezda, E. Beil, H. Bell‐Brunson, H. Benham, S. Benseler, L. Bermudez‐Santiago, W. Bernal, T. Bigley, C. Bingham, B. Binstadt, C. Black, B. Blackmon, M. Blakley, J. Bohnsack, A. Boneparth, H. Bradfield, J. Bridges, E. Brooks, M. Brothers, D. Brown, H. Brunner, L. Buckley, Mary Buckley, Meredith Buckley, H. Bukulmez, D. Bullock, A. Cancino, S. Canna, L. Cannon, S. Canny, V. Cartwright, E. Chalom, Johanna Chang, Joyce Chang, M. Chang, A. Chang‐Hoftman, A. Chen, P. Chiraseveenuprapund, K. Ciaglia, M. Cidon, D. Co, E. Cohen, R. Connor, K. Cook, A. Cooper, J. Cooper, K. Corbin, C. Correll, R. Cron, M. Curry, A. Dagci, A. Dalrymple, E. Datyner, T. Davis, D. De Ranieri, J. Dean, C. DeCoste, F. Dedeoglu, M. DeGuzman, N. Delnay, E. L. DeSantis, R. Devine, M. Dhalla, A. Dhanrajani, D. Dissanayake, B. Dizon, J. Drew, K. Driest, Q. Du, E. Duncan, K. Dunnock, D. Durkee, J. Dvergsten, A. Eberhard, K. Ede, B. Edelheit, C. Edens, M. Elder, Y. Elzaki, C. Failing, D. Fair, L. Favier, B. Feldman, J. Fennell, I. Ferguson, P. Ferguson, C. Figueroa, E. Flanagan, L. Fogel, E. Fox, M. Fox, L. Franklin, R. Fuhlbrigge, J. Fuller, T. Futch‐West, S. Gagne, M. Geiszler, D. Gerstbacher, M. Gilbert, A.C. Gironella, D. Glaser, I. Goh, S. Gorry, N. Goswami, B. Gottlieb, T. Graham, S. Grevich, T. Griffin, A. Grim, A. Grom, M. Guevara, L. Guzman, T. Hahn, O. Halyabar, E. Hammelev, T. Hammond, S. Haro, J. Harris, O. Harry, J. Hausmann, A. Hay, K. Hays, K. Hayward, L. Henderson, M. Henrickson, A. Hersh, L. Hiraki, M. Hiskey, P. Hobday, C. Hoffart, M. J. Holland, M. Hollander, S. Hong, D. Horton, J. Hsu, A. Huber, J. Huggins, J. Hui‐Yuen, M. Ibarra, A. Imlay, L. Imundo, C. Inman, A. Jackson, K. James, G. Janow, Y. Jiang, L. Johnson, N. Johnson, J. Jones, D. Kafisheh, K. Kaidar, S. Kasinathan, R. Kaur, E. Kessler, B. Kienzle, S. Kim, Y. Kimura, D. Kingsbury, M. Kitcharoensakkul, J. Klauss, K. Klein, M. Klein‐Gitelman, A. Knight, L. Kovalick, D. Krajewski, C. Kremer, T. LaFlam, B. Lang, S. Lapidus, B. Lapin, A. Lasky, E. Lawson, R. Laxer, A. Lee, Patricia Lee, Pui Lee, T. Lee, E. Leisinger, L. Lentini, M. Lerman, Y. Levinsky, D. Levy, S. Li, S. Lieberman, L. Lim, E. Limenis, C. Lin, N. Ling, G. Lionetti, R. Livny, M. Lo, A. Long, M. Lopez‐Peña, D. Lovell, S. Lvovich, A. Lytch, M. Ma, A. Machado, J. MacMahon, J. Madison, M. Mannion, C. Manos, L. Mansfield, B. Marston, K. Marzan, T. Mason, S. Matossian, L. McAllister, K. McBrearty, D. McCurdy, K. McDaniels, J. McDonald, L. McIntosh, E. Meidan, E. Mellins, Z. Mian, P. Miettunen, M. Miller, D. Milojevic, R. Mitacek, R. Modica, S. Mohan, K. Moore, T. Moore, L. Moorthy, J. Moreno, E. Morgan, A. Moyer, B. Murante, A. Murphy, E. Muscal, O. Mwizerwa, A. Najafi, K. Nanda, L. Nassi, S. Nativ, M. Natter, J. Neely, L. Newhall, A. Nuyen, P. Nigrovic, J. Nocton, B. Nolan, A. Nowakowski, K. Nowicki, R. Oakes, E. Oberle, S. Ogbonnaya‐Whittesley, E. Ogbu, M. Oliver, R. Olveda, K. Onel, A. Orandi, J. Padam, N. Pan, J. Pandya, S. Panupattanapong, A. Pappo Toledano, J. Patel, P. Patel, A. Patrick, S. Patrizi, S. Paul, J. Perfetto, M. Perron, M. Peskin, C. Pinotti, L. Ponder, R. Pooni, S. Prahalad, M. Quinlan‐Waters, J. Rafko, H. Rahimi, S. Ramsey, R. Randell, L. Ray, Ann Reed, Annelle Reed, H. Reid, D. Reiff, I. Reyhan, B. Richard, M. Riebschleger, E. Rife, M. Riskalla, A. Robinson, L. Robinson, L. Rodgers, M. Rodriquez, D. Rogers, T. Ronis, A. Rosado, M. Rosenkranz, N. Rosenwasser, H. Rothermel, D. Rothman, E. Rothschild, K. Rouster ‐ Stevens, T. Rubinstein, N. Ruth, S. Sabbagh, R. Sadun, L. Santiago, V. Saper, A. Sarkissian, L. Scalzi, J. Schahn, K. Schikler, A. Schlefman, B. Schlichting, H. Schmeling, E. Schmitt, G. Schulert, C. Schutt, C. Seper, B. Shaham, R. Sheets, A. Shehab, S. Shenoi, M. Sherman, J. Shirley, M. Shishov, N. Singer, V. Sivaraman, E. Sloan, C. Smith, J. Smith, E. Smitherman, J. Soep, M. B. Son, C. Spencer, L. Spiegel, J. Spitznagle, H. Srinivasalu, H. Stapp, A. Stephens, Y. Sterba Rakovchik, S. Stern, B. Stevens, R. Stevenson, C. Stingl, M. Stoll, E. Stringer, S. Sule, J. Sullivan, R. Sundel, M. Sutter, C. Swaffar, N. Swayne, T. Symington, G. Syverson, A.M. Szymanski, S. Taber, R. Tal, A. Tambralli, A. Taneja, T. Tanner, S. Tarvin, A. Taxter, M. Tesher, T. Thakurdeen, A. Theisen, G. Thieroff, B. Thomas, L. Thomas, N. Thomas, L. Timmerman, T. Ting, C. Todd, D. Toib, K. Torok, H. Tory, M. Toth, E. Treemarcki, S. Tse, T. Tse, C. Tsin, J. Twachtman‐Bassett, M. Twilt, T. Valcarcel, R. Valdovinos, A. Vallee, H. Van Mater, S. Vandenbergen, C. Varghese, N. Vasquez, P. Vega‐Fernandez, J. Verbsky, R. Verstegen, E. von Scheven, S. Vora, L. Wagner‐Weiner, D. Wahezi, S. Wakefield, B. Walker, S. Wallgren, H. Walters, M. Waterfield, J. Weiss, P. Weiss, E. Wershba, V. Westheuser, K. Widrick, C. Williams, S. Wong, S. Wooldridge, L. Woolnough, T. Wright, E. Wu, A. Yalcindag, R. Yeung, K. Yomogida, A. Zeft, Y. J. Zhang, Y. D. Zhao, Z. Zheng, A. Zhu, C. Zic +448 morewiley +1 more sourceConvergence in Mississippi: A Spatial Approach. [PDF]
Mississippi constitutes an interesting case study for analyzing the income convergence process because of several characteristics, such as the fairly large number of counties, its relative homogeneous economy and its low percapita income compared with ...Mihai Nicacore Local convergence for composite Chebyshev-type methods
Communications in Advanced Mathematical Sciences, 2018 We replace Chebyshev's method for solving equations requiring the second derivative by a Chebyshev-type second derivative free method. The local convergence analysis of the new method is provided using hypotheses only on the first derivative in contrast ...Santhosh George, İoannis K Argyrosdoaj +1 more sourceA Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT
This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.Afreen Islam, Anthony Siming Chen, Guido Herrmann +2 morewiley +1 more sourceHeterogeneous Convergence [PDF]
We use U.S. county-level data containing 3,058 cross-sectional observations and 41 conditioning variables to study economic growth and explore possible heterogeneity in growth determination across 32 individual states.Daniel Levy, Matthew J. Higgins, Andrew T. Young +2 morecore
