Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Ahmadzadeh, Azim"'
Autor:
Ahmadzadeh, Azim, Angryk, Rafal A.
The class-imbalance issue is intrinsic to many real-world machine learning tasks, particularly to the rare-event classification problems. Although the impact and treatment of imbalanced data is widely known, the magnitude of a metric's sensitivity to
Externí odkaz:
http://arxiv.org/abs/2206.09981
Solar flares not only pose risks to outer space technologies and astronauts' well being, but also cause disruptions on earth to our hight-tech, interconnected infrastructure our lives highly depend on. While a number of machine-learning methods have
Externí odkaz:
http://arxiv.org/abs/2206.07197
Autor:
Nita, Gelu, Ahmadzadeh, Azim, Criscuoli, Serena, Davey, Alisdair, Gary, Dale, Georgoulis, Manolis, Hurlburt, Neal, Kitiashvili, Irina, Kempton, Dustin, Kosovichev, Alexander, Martens, Piet, McGranaghan, Ryan, Oria, Vincent, Reardon, Kevin, Sadykov, Viacheslav, Timmons, Ryan, Wang, Haimin, Wang, Jason T. L.
Solar and Heliosphere physics are areas of remarkable data-driven discoveries. Recent advances in high-cadence, high-resolution multiwavelength observations, growing amounts of data from realistic modeling, and operational needs for uninterrupted sci
Externí odkaz:
http://arxiv.org/abs/2203.09544
Autor:
Yeoleka, Atharv, Patel, Sagar, Talla, Shreejaa, Puthucode, Krishna Rukmini, Ahmadzadeh, Azim, Sadykov, Viacheslav M., Angryk, Rafal A.
The Space-Weather ANalytics for Solar Flares (SWAN-SF) is a multivariate time series benchmark dataset recently created to serve the heliophysics community as a testbed for solar flare forecasting models. SWAN-SF contains 54 unique features, with 24
Externí odkaz:
http://arxiv.org/abs/2109.14770
General-purpose object-detection algorithms often dismiss the fine structure of detected objects. This can be traced back to how their proposed regions are evaluated. Our goal is to renegotiate the trade-off between the generality of these algorithms
Externí odkaz:
http://arxiv.org/abs/2105.14572
One of the limiting factors in training data-driven, rare-event prediction algorithms is the scarcity of the events of interest resulting in an extreme imbalance in the data. There have been many methods introduced in the literature for overcoming th
Externí odkaz:
http://arxiv.org/abs/2105.07532
Autor:
Ahmadzadeh, Azim, Aydin, Berkay, Georgoulis, Manolis K., Kempton, Dustin J., Mahajan, Sushant S., Angryk, Rafal A.
We present a case study of solar flare forecasting by means of metadata feature time series, by treating it as a prominent class-imbalance and temporally coherent problem. Taking full advantage of pre-flare time series in solar active regions is made
Externí odkaz:
http://arxiv.org/abs/2103.07542
Autor:
Georgoulis, Manolis K., Yardley, Stephanie L., Guerra, Jordan A., Murray, Sophie A., Ahmadzadeh, Azim, Anastasiadis, Anastasios, Angryk, Rafal, Aydin, Berkay, Banerjee, Dipankar, Barnes, Graham, Bemporad, Alessandro, Benvenuto, Federico, Bloomfield, D. Shaun, Bobra, Monica, Campi, Cristina, Camporeale, Enrico, DeForest, Craig E., Emslie, A. Gordon, Falconer, David, Feng, Li, Gan, Weiqun, Green, Lucie M., Guastavino, Sabrina, Hapgood, Mike, Kempton, Dustin, Kitiashvili, Irina, Kontogiannis, Ioannis, Korsos, Marianna B., Leka, K.D., Massa, Paolo, Massone, Anna Maria, Nandy, Dibyendu, Nindos, Alexander, Papaioannou, Athanasios, Park, Sung-Hong, Patsourakos, Spiros, Piana, Michele, Rawafi, Nour E., Sadykov, Viacheslav M., Toriumi, Shin, Vourlidas, Angelos, Wang, Haimin, L. Wang, Jason T., Whitman, Kathryn, Yan, Yihua, Zhukov, Andrei N.
Publikováno v:
In Advances in Space Research February 2024
Autor:
Nita, Gelu, Georgoulis, Manolis, Kitiashvili, Irina, Sadykov, Viacheslav, Camporeale, Enrico, Kosovichev, Alexander, Wang, Haimin, Oria, Vincent, Wang, Jason, Angryk, Rafal, Aydin, Berkay, Ahmadzadeh, Azim, Bai, Xiaoli, Bastian, Timothy, Boubrahimi, Soukaina Filali, Chen, Bin, Davey, Alisdair, Fereira, Sheldon, Fleishman, Gregory, Gary, Dale, Gerrard, Andrew, Hellbourg, Gregory, Herbert, Katherine, Ireland, Jack, Illarionov, Egor, Kuroda, Natsuha, Li, Qin, Liu, Chang, Liu, Yuexin, Kim, Hyomin, Kempton, Dustin, Ma, Ruizhe, Martens, Petrus, McGranaghan, Ryan, Semones, Edward, Stefan, John, Stejko, Andrey, Collado-Vega, Yaireska, Wang, Meiqi, Xu, Yan, Yu, Sijie
The authors of this white paper met on 16-17 January 2020 at the New Jersey Institute of Technology, Newark, NJ, for a 2-day workshop that brought together a group of heliophysicists, data providers, expert modelers, and computer/data scientists. The
Externí odkaz:
http://arxiv.org/abs/2006.12224
Autor:
Ahmadzadeh, Azim, Hostetter, Maxwell, Aydin, Berkay, Georgoulis, Manolis K., Kempton, Dustin J., Mahajan, Sushant S., Angryk, Rafal A.
In analyses of rare-events, regardless of the domain of application, class-imbalance issue is intrinsic. Although the challenges are known to data experts, their explicit impact on the analytic and the decisions made based on the findings are often o
Externí odkaz:
http://arxiv.org/abs/1911.09061