Search

Your search keyword '"Stoica, George"' showing total 644 results
Start Over Author "Stoica, George"
644 results on '"Stoica, George"'

1. Model merging with SVD to tie the Knots

Author

Stoica, George, Ramesh, Pratik, Ecsedi, Boglarka, Choshen, Leshem, and Hoffman, Judy

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Recent model merging methods demonstrate that the parameters of fully-finetuned models specializing in distinct tasks can be combined into one model capable of solving all tasks without retraining. Yet, this success does not transfer well when merging LoRA finetuned models. We study this phenomenon and observe that the weights of LoRA finetuned models showcase a lower degree of alignment compared to their fully-finetuned counterparts. We hypothesize that improving this alignment is key to obtaining better LoRA model merges, and propose KnOTS to address this problem. KnOTS uses the SVD to jointly transform the weights of different LoRA models into an aligned space, where existing merging methods can be applied. In addition, we introduce a new benchmark that explicitly evaluates whether merged models are general models. Notably, KnOTS consistently improves LoRA merging by up to 4.3% across several vision and language benchmarks, including our new setting. We release our code at: https://github.com/gstoica27/KnOTS.

Published
2024

2. IMAGING ANALYSIS OF PERIODONTAL STATUS IN A GROUP OF PATIENTS WITH OSTEOPOROSIS

Author

Stoica George, Roxana Popescu, Andreea Diana Ilinca, Daniela Pomohaci, Balcos Carina, Alexandru Nemtoi, Sirghe Ana, and Haba Danisia

Subjects
osteoporosis, panoramic radiography, bone density, Dentistry, RK1-715
Abstract

Osteoporosis, a systemic disorder characterized by reduced bone density and microarchitectural deterioration, significantly affects bone health, including the mandibular and periodontal structures. This study aimed to evaluate the relationship between osteoporosis and periodontal pathology using imaging techniques in patients diagnosed with osteoporosis. Material and methods: The retrospective, descriptive study included 63 patients diagnosed with osteoporosis and other systemic conditions. Periodontal status was assessed clinically and paraclinically using the EGOHID evaluation system, while bone density was evaluated radiographically using indices such as the Mandibular Cortical Index (MCI), Mental Index (MI), Panoramic Mandibular Index (PMI), and Mandibular Cortical Width (MCW). Results: Results revealed significant periodontal involvement, with 42.9% of patients exhibiting moderate chronic marginal periodontitis and 46% severe periodontitis, more pronounced in the maxillary arch than the mandibular. Radiographic evaluation demonstrated that 58.7% of patients with osteoporosis had a slightly eroded mandibular cortex (C2), while 34.9% showed severe erosion (C3). The average cortical thickness (MCW) was significantly reduced in osteoporotic patients compared to non-osteoporotic individuals, highlighting its potential as a screening indicator. Conclusions: Osteoporosis is strongly associated with significant periodontal alterations and mandibular cortical resorption. These findings underline the importance of integrating bone health assessments into periodontal evaluations, emphasizing the role of imaging as a non-invasive screening tool for osteoporosis.

Published
2024
Full Text
View/download PDF

3. Analyzing domain shift when using additional data for the MICCAI KiTS23 Challenge

Author

Stoica, George, Breaban, Mihaela, and Barbu, Vlad

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Using additional training data is known to improve the results, especially for medical image 3D segmentation where there is a lack of training material and the model needs to generalize well from few available data. However, the new data could have been acquired using other instruments and preprocessed such its distribution is significantly different from the original training data. Therefore, we study techniques which ameliorate domain shift during training so that the additional data becomes better usable for preprocessing and training together with the original data. Our results show that transforming the additional data using histogram matching has better results than using simple normalization., Comment: This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution is published in https://link.springer.com/book/10.1007/978-3-031-54806-2, and is available online at https://doi.org/10.1007/978-3-031-54806-2_4

Published
2023
Full Text
View/download PDF

4. ZipIt! Merging Models from Different Tasks without Training

Author

Stoica, George, Bolya, Daniel, Bjorner, Jakob, Ramesh, Pratik, Hearn, Taylor, and Hoffman, Judy

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Typical deep visual recognition models are capable of performing the one task they were trained on. In this paper, we tackle the extremely difficult problem of combining distinct models with different initializations, each solving a separate task, into one multi-task model without any additional training. Prior work in model merging permutes one model to the space of the other then averages them together. While this works for models trained on the same task, we find that this fails to account for the differences in models trained on disjoint tasks. Thus, we introduce "ZipIt!", a general method for merging two arbitrary models of the same architecture that incorporates two simple strategies. First, in order to account for features that aren't shared between models, we expand the model merging problem to allow for merging features within each model by defining a general "zip" operation. Second, we add support for partially zipping the models up until a specified layer, naturally creating a multi-head model. We find that these two changes combined account for 20-60% improvement over prior work, making it more feasible to merge models trained on disjoint tasks without retraining.

Published
2023

5. Dynamic Batch Adaptation

Author

Simionescu, Cristian, Stoica, George, and Herscovici, Robert

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

Current deep learning adaptive optimizer methods adjust the step magnitude of parameter updates by altering the effective learning rate used by each parameter. Motivated by the known inverse relation between batch size and learning rate on update step magnitudes, we introduce a novel training procedure that dynamically decides the dimension and the composition of the current update step. Our procedure, Dynamic Batch Adaptation (DBA) analyzes the gradients of every sample and selects the subset that best improves certain metrics such as gradient variance for each layer of the network. We present results showing DBA significantly improves the speed of model convergence. Additionally, we find that DBA produces an increased improvement over standard optimizers when used in data scarce conditions where, in addition to convergence speed, it also significantly improves model generalization, managing to train a network with a single fully connected hidden layer using only 1% of the MNIST dataset to reach 97.79% test accuracy. In an even more extreme scenario, it manages to reach 97.44% test accuracy using only 10 samples per class. These results represent a relative error rate reduction of 81.78% and 88.07% respectively, compared to the standard optimizers, Stochastic Gradient Descent (SGD) and Adam.

Published
2022

7. Understanding the Meaning of the Equal Sign: A Case Study of Middle School Students in the United Arab Emirates

Author

Wardat, Yousef, Jarrah, Adeeb M., and Stoica, George

Abstract

The equal symbol has been used in diverse mathematical frameworks, such as arithmetic, algebra, trigonometry, set theory, and so on. In mathematical terms, the equal sign has been used in fixed command of standings. The study reports on the students meaning and interpretations of the equal sign. The study involved Grade 6, 7, and 8 students in a secondary school in Alain, United Arab Emirates (UAE). Much of the earlier research done on the equal sign has focused on the primary school level, but this one focuses on middle school students. The study shows that the maximum foremost understanding of the equal sign amongst Grade 6, 7, and 8 students is a do-something, unidirectional symbol. Students realize the equal sign as an instrument for marking the response moderately than as an interpersonal symbol to associate extents.

Published
2021

8. Re-TACRED: Addressing Shortcomings of the TACRED Dataset

Author

Stoica, George, Platanios, Emmanouil Antonios, and Póczos, Barnabás

Subjects
Computer Science - Computation and Language
Abstract

TACRED is one of the largest and most widely used sentence-level relation extraction datasets. Proposed models that are evaluated using this dataset consistently set new state-of-the-art performance. However, they still exhibit large error rates despite leveraging external knowledge and unsupervised pretraining on large text corpora. A recent study suggested that this may be due to poor dataset quality. The study observed that over 50% of the most challenging sentences from the development and test sets are incorrectly labeled and account for an average drop of 8% f1-score in model performance. However, this study was limited to a small biased sample of 5k (out of a total of 106k) sentences, substantially restricting the generalizability and broader implications of its findings. In this paper, we address these shortcomings by: (i) performing a comprehensive study over the whole TACRED dataset, (ii) proposing an improved crowdsourcing strategy and deploying it to re-annotate the whole dataset, and (iii) performing a thorough analysis to understand how correcting the TACRED annotations affects previously published results. After verification, we observed that 23.9% of TACRED labels are incorrect. Moreover, evaluating several models on our revised dataset yields an average f1-score improvement of 14.3% and helps uncover significant relationships between the different models (rather than simply offsetting or scaling their scores by a constant factor). Finally, aside from our analysis we also release Re-TACRED, a new completely re-annotated version of the TACRED dataset that can be used to perform reliable evaluation of relation extraction models.

Published
2021

9. Improving Relation Extraction by Leveraging Knowledge Graph Link Prediction

Author

Stoica, George, Platanios, Emmanouil Antonios, and Póczos, Barnabás

Subjects
Computer Science - Computation and Language
Abstract

Relation extraction (RE) aims to predict a relation between a subject and an object in a sentence, while knowledge graph link prediction (KGLP) aims to predict a set of objects, O, given a subject and a relation from a knowledge graph. These two problems are closely related as their respective objectives are intertwined: given a sentence containing a subject and an object o, a RE model predicts a relation that can then be used by a KGLP model together with the subject, to predict a set of objects O. Thus, we expect object o to be in set O. In this paper, we leverage this insight by proposing a multi-task learning approach that improves the performance of RE models by jointly training on RE and KGLP tasks. We illustrate the generality of our approach by applying it on several existing RE models and empirically demonstrate how it helps them achieve consistent performance gains.

Published
2020

12. PROBLEMS

Author

Missouri State University Problem Solving Group, Hung, Tran Quang, Kórus, Péter, Garcia, Antonio, Ioan, Băetu, Fusaro, Ben, Loase, John, Gökçe, Lokman, Hall, Timothy, Kouba, Omran, Stewart, Séan M., Bradie, Brian, Dey, Souvik, Stoica, George, Perdomo, Francisco, Plaza, Ángel, Downes, Rob, and Schwartz, Randy K.

Published
2021

13. 12282

Author

Stoica, George

Published
2021

15. PROBLEMS

Author

Northwestern University Math Problem Solving Group, Missouri State University Problem Solving Group, Channakeshava, M. V., Stuart, Jeff, Stoica, George, Coll, Vincent, Conus, Daniel, Stanescu, Florin, Fondanaiche, Philippe, Plaza, Ángel, Goldenberg, Michael, Stadler, Albert, Moore, Donald Jay, Herman, Eugene A., Kórus, Péter, Budney, Paul, Tetiva, Marian, and Bataille, Michel

Published
2021

17. Asking the classroom with technology: a systematic literature review.

Author

Alam, Talha Mahboob, Stoica, George Adrian, and Özgöbek, Özlem

Subjects
CORE competencies, DIGITAL literacy, TECHNICAL literature, DIGITAL divide, RESOURCE allocation, STUDENT response systems
Abstract

Response technologies (RTs), also termed clickers or student response systems, have gained traction among researchers in classrooms in recent years. RTs encompass various interactive tools and technologies that are pivotal in modern educational settings. Numerous articles emphasize the effectiveness of RTs across multiple grades and courses. Existing literature reviews on the subject need a systematic review from a school classroom perspective. This article aims to present a systematic review of the literature on the effectiveness of RTs in school classrooms and highlight future guidelines for implementing RTs. We conducted a systematic literature review, collecting 105 peer-reviewed studies covering different school grades and courses. Our work presented the mapping of RTs, a graphical summary of our work, the applications of RTs in major courses at primary, middle, and high school levels, and future guidelines for implementing RTs in school classrooms under one umbrella. A significant number of studies reported positive learning outcomes. Still, few studies reported insignificant learning outcomes due to the digital divide, deficiency of proper infrastructure, limited support for innovative practices, lack of compatibility with other existing platforms, and inadequate digital literacy. This study provides recommendations for technologists (human-centered design, dynamic customization, advanced data protection protocols, cross-platform adaptability), teachers (digital competence, lecture planning, peer collaboration, adaptive teaching), institutions (resources allocation, support of interactive practices, impact monitoring, incentives for teachers) policymakers (training programs, equitable access, funding, and resources, clear guidelines for implementation) for successful implementation. [ABSTRACT FROM AUTHOR]

Published
2025
Full Text
View/download PDF

18. PROBLEMS

Author

Wong, Fook Sung, Sabihi, Ahmad, Omarjee, Moubinool, Berstis, Victors, Dresden, Gregory, Gazin, Jackson, McNeill, Kathleen, Stoica, George, Furdui, Ovidiu, Sîntămărian, Alina, Tetiva, Marian, Calcaterra, Robert, Stewart, Seán M., Kouba, Omran, Siehler, Jacob, Nieto, José Heber, Kumar, Sushanth Sathish, Merca, Mircea, and Gordon, Russell

Published
2021

22. PROBLEMS

Author

REID, LES, IONAŞCU, EUGEN J., BELSHOFF, RICHARD, GHANDEHARI, MAHYA, PALSSON, EYVINDUR ARI, RATCLIFF, GAIL, VALDEZ, ROGELIO, Hall, Timothy, Stewart, Seán M., Dey, Souvik, Stoica, George, Downes, Rob, Ohtsuka, Hideyuki, Jakimczuk, Rafael, Băetu, Ioan, Budney, Paul, Nievergelt, Yves, Vowe, Michael, Bracken, Paul, Goldenberg, Michael, Kaplan, Mark, Ionescu, Andrei, Schmeichel, Edward, Stanescu, Florin, and Christopher, John

Published
2020

23. 12212

Author

Stoica, George

Published
2020

24. PROBLEMS

Author

Missouri State University Problem Solving Group, UTSA Problem Solving Club, Goldenberg, Michael, Kaplan, Mark, Moore, Donald Jay, Kórus, Péter, Tetiva, Marian, Lampakis, Elias, Stoica, George, Calcaterra, Robert, Stadler, Albert, Zhou, Li, Schacht, Celia, Stanescu, Florin, Furdui, Ovidiu, Sîntămărian, Alina, Herman, Eugene, and Pratt, Rob

Published
2020

29. PROBLEMS

Author

Tetiva, Marian, Stewart, Seán M., Siehler, Jacob, Stoica, George, Merca, Mircea, Bencze, Mihàly, Ehrenborg, Richard, Jager, Tom, Bojaxhiu, Elton, Calcaterra, Robert, Furdui, Ovidiu, Sîntămariăn, Alina, Viscusi, Jake, Delacroix, Eugene, Treviño, Enrique, and Cowieson, Bill

Published
2020

30. Antibiotic Resistance Pattern of Pathogens Isolated from Pediatric Patients during and after the COVID-19 Pandemic.

Author

Golli, Andreea-Loredana, Popa, Simona Georgiana, Cara, Monica Laura, Stoica, George-Alin, Fortofoiu, Dragos, and Stoica, Maria

Subjects
PEDIATRIC intensive care, GRAM-negative bacteria, CHILD patients, HOSPITAL care of children, COVID-19 pandemic
Abstract

Background/Objectives: The present study aims to highlight the possible significant changes due to the COVID-19 pandemic in the resistance of pathogens involved in cases of pediatric infections. Methods: This study included children hospitalized in the Pediatric Intensive Care Unit, Surgery and Pediatrics from a tertiary teaching hospital, during and after the COVID-19 period (2020–2023). Results: The research included 845 samples collected during 2020–2023, from 685 pediatric patients. A total of 937 bacterial isolates were obtained, of which 509 isolates (54.32%) were Gram-negative bacteria. Around 30% of all the pathogens were multidrug-resistant (MDR), with a statistically significant increase post-pandemic, in the case of the MDR Escherichia coli strains (p < 0.05). A very high percentage of MDR Acinetobacter spp. isolates was found, with an important, but not statistically significant, increase in the post-pandemic period. The highest percentage of the MDR Gram-positive pathogens was registered in the case of S. aureus strains (31.80%). Over 20% of the Coagulase-negative Staphylococci (CoNS) strains isolated between 2020 and 2023 were MDR, with an important increase in the post-COVID-19 period. The proportion of carbapenem-resistant Gram-negative pathogens significantly decreased in the post-COVID-19 period compared with the COVID-19 period (p < 0.05), especially in the case of the Klebsiella spp. strains. Conclusions: Our findings revealed the increase in the post-COVID-19 period of the prevalence of MDR strains of Acinetobacter spp., CoNS, and Escherichia coli isolated in pediatric patient samples and a significant decline in the trend of the carbapenem-resistant Gram-negative pathogens, which may be due to the testing rate and to the specific pathology of the pediatric patients hospitalized in the two periods. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

32. PROBLEMS

Author

Northwestern University Math Problem Solving Group, Bradley, David M., Stanescu, Florin, Merca, Mircea, Mabry, Rick, Dresden, Gregory, Stoica, George, Gheroghe, Oniciu, Nieto, José Heber, Trevi˜no, Enrique, DeBacco, Cassandra, Capsambelis, Mark, Furdui, Ovidiu, Sîntămărian, Alina, Băetu, Ioan, Reid, Michael, Mero, Su Pernu, and Cowieson, Bill

Published
2020

35. 12152

Author

Stoica, George

Published
2019

36. PROBLEMS

Author

The Iowa State Undergraduate Problem Solving Group, GWstat Problem Solving Group, Băetu, Ioan, Nievergelt, Yves, Bracken, Paul, Ionescu, Andrei, Stanescu, Florin, Omarjee, Moubinool, Stoica, George, Shabani, Armend Sh., Nieto, José Heber, Treviño, Enrique, Dresden, Gregory, Islam, Saimon, Zhang, Jiahao, Calcaterra, Robert, Wu, Andrew, Gatesman, Kyle, and Mero, Su Pernu

Published
2019

37. PROBLEMS

Author

Skidmore College Problem Group, Băetu, Ioan, Sorel, Julien, Treviño, Enrique, Do, Bao, Goldenberg, Michael, ShahAli, H. A., Furdui, Ovidiu, Sîntămărian, Alina, DiMuro, Joseph, Stoica, George, Sahoo, Nikhil, Gao, Xueshi, Kominers, Scott Duke, Kim, Jimin, and Kim, Sung Soo

Published
2019

39. PROBLEMS

Author

Northwestern University Math Problem Solving Group, Stoica, George, Bojaxhiu, Elton, Furdui, Ovidiu, Sîntămariăn, Alina, Delacroix, Eugene, Treviño, Enrique, Stephens, Richard, Gaitanas, Konstantinos, Mitrofanov, Vadim, Mabry, Rick, Shepherd, Debbie, Oman, Greg, Jager, Tom, Herman, Eugene A., Levasseur, Kenneth, Raymond, Nicholas, and Reid, Michael

Published
2019

42. Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

Author

Elbert, Alicia, Vallejos, Augusto, Alvarisqueta, Andres, Maffei, Laura, Juncos, Luis, de Arteaga, Javier, Greloni, Gustavo, Farias, Eduardo, Zucchini, Alfredo, Vogel, Daniel, Cusumano, Ana, Santos, Juan, Fraenkel, Margaret, Gallagher, Martin, Davis, Tim, Acharya, Shamasunder, Cooke, Duncan, Suranyi, Michael, Roger, Simon, Toussaint, Nigel, Pollock, Carol, Chan, Doris, Stranks, Stephen, MacIsaac, Richard, Endre, Zoltan, Schmidt, Alice, Prager, Rudolf, Mayer, Gert, Warling, Xavier, Jadoul, Michel, Hougardy, Jean, Vercammen, Chris, Van Vlem, Bruno, Gillard, Pieter, Costa e Forti, Adriana, Borges, Joao Lindolfo, Santos Canani, Luis, Eliaschewitz, Freddy, Leite, Silmara, Fraige Filho, Fadlo, Paschoalin, Raphael, Moura Neto, Jose Andrade, Deboni, Luciane, de Lourdes Noronha, Irene, Cercato, Cintia, Prompt, Carlos Alberto, Zanella, Maria, Rassi, Nelson, D'Avila, Domingos, Milagres, Rosangela, Felicio, Joao, Pecoits Filho, Roberto, Riella, Miguel Carlos, Salles, Joao, Keitel, Elizete, Draibe, Sergio, Amodeo, Celso, Youmbissi, Joseph, Roy, Louise, Cournoyer, Serge, Jolly, Shivinder, Pichette, Vincent, Nesrallah, Gihad, Bajaj, Harpreet Singh, Khandwala, Hasnain, Aronson, Ronnie, Goluch, Richard, Tam, Paul, Rabbat, Christian, Tobe, Sheldon, Bailey, Gordon, Chow, Stephen, Castillo, Alvaro, Danin Vargas, Alfredo, Gonzalez, Fernando, Munoz, Rodrigo, Gutierrez, Vicente, Godoy, Gonzalo, Zhao, Hongwen, Liu, Zhangsuo, Zhao, Minghui, Guo, Xiaohui, Su, Benli, Fu, Shuxia, Xu, Yan, Yang, Jinkui, Shi, Bingyin, Xiao, Guanqing, Shi, Wei, Hao, Chuanming, Xing, Changying, Hou, Fanfan, Luo, Qun, Li, Yuxiu, Ji, Linong, Zuo, Li, Wang, Song, Ni, Zhaohui, Ding, Guohua, Chen, Nan, Zhao, Jiajun, Jia, Weiping, Yu, Shengqiang, Weng, Jian, Xu, Gang, Fu, Ping, Sun, Shiren, Liu, Bicheng, Ding, Xiaoqiang, Rychlik, Ivan, Oplustilova, Alexandra, Bartaskova, Dagmar, Honova, Vaclava, Chmelickova, Hana, Petr, Martin, Bucek, Petr, Tesar, Vladimir, Zahumensky, Emil, Povlsen, Johan, Egstrup, Kenneth, Oczachowska-Kulik, Anna, Rossing, Peter, Lahtela, Jorma, Strand, Jorma, Kantola, Ilkka, Petit, Catherine, Combe, Christian, Zaoui, Philippe, Esnault, Vincent, Urena Torres, Pablo, Halimi, Jean-Michel, Dussol, Bertrand, Bieler, Tasso, Budde, Klemens, Dellanna, Frank, Segiet, Thomas, Kosch, Christine, Schmidt-Guertler, Hans, Schenkenberger, Isabelle, Vielhauer, Volker, Pistrosch, Frank, Alscher, Mark, Hasslacher, Christoph, Hugo, Christian, Muehlfeld, Anja, Wanner, Christoph, Passadakis, Ploumis, Apostolou, Theofanis, Tentolouris, Nikolaos, Stefanidis, Ioannis, Mavromatidis, Konstantinos, Liakopoulos, Vasilios, Goumenos, Dimitrios, Siamopoulos, Konstantinos, Yeung, Vincent, Ozaki, Risa, Fung, Samuel, Tan, Kathryn, Tang, Sydney, Lui, Sing Leung, Cheung, Siu Fai, Sreenan, Seamus, Eustace, Joseph, O'Shea, Donal, Lavin, Peter, Stack, Austin, Yagil, Yoram, Wainstein, Julio, Knobler, Hilla, Cohen, Josef, Kenis, Irina, Daoud, Deeb, Bar-Dayan, Yosefa, Frajewicki, Victor, Adawi, Faiad, Gesualdo, Loreto, Santoro, Domenico, Marino, Francesco, Galfre, Andrea, Brunati, Chiara, Ruggenenti, Piero, Rombola, Giuseppe, Pugliese, Giuseppe, Ravera, Maura, Malberti, Fabio, Pontoriero, Giuseppe, Rampino, Teresa, De Cosmo, Salvatore, Esposito, Ciro, Nappi, Felice, Abaterusso, Cataldo, Conte, Giuseppe, Panichi, Vincenzo, Lauro, Davide, Capasso, Giovambattista, Russo, Domenico, Anzai, Jiichi, Naka, Motoji, Ato, Keita, Tsujimoto, Tetsuro, Nimura, Toshinori, Nakashima, Eitaro, Takeda, Tetsuro, Fujii, Shinya, Kobayashi, Kunihisa, Iwaoka, Hideaki, Nagayama, Koji, Harada, Hiroyuki, Maeda, Hajime, Kishimoto, Rui, Iitsuka, Tadashi, Itabashi, Naoki, Furuya, Ryuichi, Maeda, Yoshitaka, Yamada, Daishiro, Sasaki, Nobuhiro, Sasaki, Hiromitsu, Ueda, Shinichiro, Kashihara, Naoki, Watanabe, Shuichi, Nakamura, Takehiro, Kanai, Hidetoshi, Makita, Yuichiro, Ono, Keiko, Iehara, Noriyuki, Goto, Daisuke, Kosuge, Keiichiro, Tsuchida, Kenichi, Sato, Toshiaki, Sekikawa, Takashi, Okamoto, Hideki, Tanaka, Tsuyoshi, Ikeda, Naoko, Tadika, Takenobu, Mukasa, Koji, Osonoi, Takeshi, Hirano, Fuminori, Nishimura, Motonobu, Yambe, Yuko, Tanaka, Yukio, Ujihara, Makoto, Sakai, Takashi, Imura, Mitsuo, Umayahara, Yutaka, Makino, Shinya, Nakazawa, Jun, Yamaguchi, Yukinari, Kashine, Susumu, Miyaoka, Hiroaki, Suzuki, Katsunori, Inoue, Toshihiko, Nagai, Sou, Sato, Nobuyuki, Yamamoto, Masahiro, Taya, Noriyasu, Fujita, Akira, Matsutani, Akira, Shibagaki, Yugo, Sato, Yuichi, Yamauchi, Akira, Tsutsui, Masahiro, Ishiko, Tamayo, Kaneko, Shizuka, Azuma, Nobuyuki, Matsuda, Hirofumi, Hashiguchi, Yasuhiro, Onishi, Yukiko, Tokui, Mikiya, Matsuhisa, Munehide, Kiyosue, Arihiro, Shinoda, Junji, Ishikawa, Kazuo, Ahmad, Ghazali, Vijayasingham, Shalini, Aziz, Nor Azizah, Hussein, Zanariah, Fung, Yin Khet, Hassan, Wan Hasnul Halimi Wan, Wong, Hin Seng, Goh, Bak Leong, Ali, Norhaliza Mohd, Merican, Nor Shaffinaz Yusuf Azmi, Vaithilingam, Indralingam, Nik Ahmad, Nik Nur Fatnoon, Adam, Noor, Sukor, Norlela, Vengadasalam, V Paranthaman P, Abdul Kadir, Khalid, Mohamed, Mafauzy, Renoirte Lopez, Karina, Leguizamo-Dimas, Aniceto, Chew Wong, Alfredo, Chevaile-Ramos, Jose, Gonzalez Gonzalez, Jose, Rico Hernandez, Raul, Nino-Cruz, Jose, Sauque Reyna, Leobardo, Gonzalez-Galvez, Guillermo, Madero Rovalo, Magdalena, Bochicchio-Ricardelli, Tomasso, Aldrete, Jorge, Carranza-Madrigal, Jaime, Vogt, Liffert, Smak Gregoor, Peter, Barendregt, JNM, Luik, Peter, Gansevoort, Ronald, Laverman, Gozewijn, Pilmore, Helen, Lunt, Helen, Baker, John, Miller, Steven, Rabindranath, Kannaiyan, Zapata-Rincon, Luis, Vargas-Gonzales, Rolando, Calderon Ticona, Jorge, Dextre Espinoza, Augusto, Burga Nunez, Jose, Zea-Nunez, Carlos Antonio, Herrada Orue, Benjamin, Medina-Santander, Boris, Delgado-Butron, Cesar, Farfan-Aspilcueta, Julio, Mazur, Stanislaw, Necki, Miroslaw, Wruk, Michal, Klodawska, Katarzyna, Popenda, Grazyna, Skokowska, Ewa, Arciszewska, Malgorzata, Wiecek, Andrzej, Ciechanowski, Kazimierz, Nowicki, Michal, Birne, Rita, Cabrita, Antonio, Ramos, Aura, Antunes Ferreira, Manuel Anibal, Matta Fontanet, Evelyn, Alcantara-Gonzalez, Altagracia Aurora, Comulada-Rivera, Angel, Galindo Ramos, Eugenia, Cangiano, Jose, Quesada-Suarez, Luis, Calderon Ortiz, Ricardo, Vazquez-Tanus, Jose, Burgos-Calderon, Rafael, Rosado, Carlos, Hancu, Nicolae, Pintilei, Ella, Mistodie, Cristina, Bako, Gabriel, Ionutiu, Lavinia, Petrica, Ligia, Timar, Romulus, Tuta, Liliana, Duma, Livia, Tutescu, Adriana, Ivanova, Svetlana, Essaian, Ashot, Zrazhevskiy, Konstantin, Tomilina, Natalia, Smolyarchuk, Elena, Kuzin, Anatoly, Lantseva, Olga, Karpova, Irina, Shamkhalova, Minara, Liberanskaya, Natalia, Yavdosyuk, Andrey, Shvarts, Yuri, Bardymova, Tatiana, Blagoveshchenskaya, Olga, Solovev, Oleg, Rechkova, Elena, Pikalova, Natalia, Pavlova, Maria, Kolmakova, Elena, Sayfutdinov, Rustam, Villevalde, Svetlana, Koziolova, Natalya, Martynenko, Vladimir, Marasaev, Vyacheslav, Maksudova, Adelya, Sigitova, Olga, Mordovin, Viktor, Klimontov, Vadim, Samoylova, Yulia, Karonova, Tatiana, Yeoh, Lee Ying, Teo, Boon Wee, Foo, Marjorie Wai Yin, Liew, Adrian, Tkac, Ivan, Oroszova, Aniko, Fekete, Jozef, Rosenberger, Jaroslav, Obetkova, Ida, Fulopova, Alla, Kolesarova, Eva, Raslova, Katarina, Smolko, Peter, Oksa, Adrian, Distiller, Larry, Trokis, Julien, Adams, Luthando, Makan, Hemant, Ramlachan, Padaruth, Mitha, Essack, Coetzee, Kathleen, Punt, Zelda, Bhorat, Qasim, Naiker, Puvenesvari, Ellis, Graham, Van Zyl, Louis, Lee, Kwan Woo, Kim, Min Seon, Yoo, Soon-Jib, Yoon, Kun Ho, Cho, Yong-Wook, Park, Tae-Sun, Kim, Sang Yong, Choi, Moon-Gi, Oh, Tae Keun, Lee, Kang-Wook, Shon, Ho Sang, Suh, Sung Hwan, Kim, Byung-Joon, Doo-Man, Kim, Yi, Joo Hark, Lee, Sang Ah, Cho, Ho Chan, Kim, Sin-Gon, Cha, Dae-Ryong, Seo, Ji A, Choi, Kyung Mook, Woo, Jeong-Taek, Ahn, Kyu Jeung, Lee, Jae Hyuk, Kim, In-Joo, Lee, Moon-Kyu, Jang, Hak Chul, Park, Kyong-Soo, Kim, Beom Seok, Mok, Ji Oh, Shin, Mijung, Yoon, Sun Ae, Nam-Goong, Il-Seong, Chung, Choon Hee, Yu, Tae Yang, Lee, Hyoung Woo, Soto Gonzalez, Alfonso, Almirall, Jaume, Egido, Jesus, Calero Gonzalez, Francesca, Fernandez Fresnedo, Gema, Valera Cortes, Ildefonso, Praga Terente, Manuel, Garcia Mendez, Isabel, Navarro Gonzalez, Juan, Herrero Calvo, Jose, Cigarran Guldris, Secundino, Prieto Velasco, Mario, Minguela Pesquera, Jose Ignacio, Galan, Antonio, Pascual, Julio, Marques Vidas, Maria, Martins Munoz, Judith, Rodriguez-Perez, Jose, Castro-Alonso, Cristina, Bonet Sol, Josep, Seron, Daniel, Fernandez Giraldez, Elvira, Arrieta Lezama, Javier, Montero, Nuria, Hernandez-Jaras, Julio, Santamaria Olmo, Rafael, Molas Coten, Jose Ramon, Hellberg, Olof, Fellstrom, Bengt, Bock, Andreas, Pei, Dee, Lin, Ching-Ling, Tien, Kai-Jen, Chen, Ching-Chu, Huang, Chien-Ning, Jiang, Ju-Ying, Wu, Du-An, Chu, Chih-Hsun, Tseng, Shih-Ting, Chen, Jung-Fu, Bau, Cho-Tsan, Sheu, Wayne, Wu, Mai-Szu, Sari, Ramazan, Sezer, Siren, Yildiz, Alaattin, Satman, Ilhan, Kalender, Betul, Mankovskyy, Borys, Fushtey, Ivan, Stanislavchuk, Mykola, Kolenyk, Mykola, Dudar, Iryna, Zolotaikina, Viktoriia, Abrahamovych, Orest, Kostynenko, Tetyana, Petrosyan, Olena, Kuskalo, Petro, Galushchak, Olga, Legun, Oleg, Topchii, Ivan, Martynyuk, Liliya, Stryzhak, Vasyl, Panina, Svitlana, Tkach, Sergii, Korpachev, Vadym, Maxwell, Peter, Gnudi, Luigi, Kon, Sui Phin, Tindall, Hilary, Kalra, Phillip, Mark, Patrick, Patel, Dipesh, El-Shahawy, Mohamed, Bai, Liqun, Nica, Romanita, Lien, Yeong-Hau, Menefee, Judson, Busch, Robert, Miller, Alan, Ahmed, Azazuddin, Arif, Ahmed, Lee, Joseph, Desai, Sachin, Bansal, Shweta, Bentsianov, Marie, Belledonne, Mario, Jere, Charles, Gaona, Raul, Greenwood, Gregory, Brusco, Osvaldo, Boiskin, Mark, Belo, Diogo, Minasian, Raffi, Atray, Naveen, Lawrence, Mary, Taliercio, John, Pergola, Pablo, Scott, David, Alvarez, German, Marder, Bradley, Powell, Thomas, Bakdash, Wa'el, Stoica, George, McFadden, Christopher, Rendell, Marc, Wise, Jonathan, Jones, Audrey, Jardula, Michael, Madu, Ivy-Joan, Varghese, Freemu, Tulloch, Brian, Ahmed, Ziauddin, Hames, Melanie, Nazeer, Imran, Shahid, Newman, John, Rekha, Montero, Manuel, Fitz-Patrick, David, Phillips, Lawrence, Guasch, Antonio, Christofides, Elena, Gundroo, Aijaz, Amin, Mohammad, Bowman-Stroud, Cynthia, Link, Michael, Mulloy, Laura, Nammour, Michael, Lalwani, Tarik, Hanson, Lenita, Whaley-Connell, Adam, Herman, Lee, Chatha, Rupi, Osama, Sayed, Liss, Kenneth, Kayali, Zeid, Bhargava, Anuj, Israel, Ezra, Peguero-Rivera, Alfredo, Fang, Michael, Slover, Judith, Barengolts, Elena, Flores, Jose, Muoneke, Rosemary, Savin, Virginia, Awua-Larbi, Stella, Levine, Andrew, Newman, George, Golestaneh, Laden, Bohm, Guillermo, Reisin, Efrain, Cruz, Lucita, Weiss, Robert, Zieve, Franklin, Horwitz, Edward, Chuang, Peale, Mersey, James, Manley, John, Graf, Ronald, Bedros, Fadi, Joshi, Sudhir, Frias, Juan, Assefi, Ali, O'Shaughnessy, Andrew, Brantley, Roman, Minga, Todd, Tietjen, David, Kantor, Samuel, Jamal, Aamir, Guadiz, Ramon, Hershon, Kenneth, Bressler, Peter, Kopyt, Nelson, Cathcart, Harold, Bloom, Scott, Reichel, Ronald, Nakhle, Samer, Dulude, Emily, Tarkan, Joshua, Baker, Penelope, Zeig, Steven, Moya Hechevarria, Jaynier, Ropero-Cartier, Armando, De la Calle, Gilda, Doshi, Ankur, Saba, Fadi, Sligh, Teresa, Shaw, Sylvia, Kumar, Jayant, Szerlip, Harold, Bayliss, George, Perlman, Alan, Sakhrani, Lakhi, Gouge, Steven, Argoud, Georges, Acosta, Idalia, Elder, John, Joshi, Sucharit, Sensenbrenner, John, Vicks, Steven, Mangoo-Karim, Roberto, Galphin, Claude, Leon-Forero, Carlos, Gilbert, John, Brown, Eric, Ijaz, Adeel, Butt, Salman, Markell, Mariana, Arauz-Pacheco, Carlos, Sloan, Lance, Alvarado, Odilon, Jabbour, Serge, Simon, Eric, Rastogi, Anjay, James, Sam, Bakris, George, Hall, Karen, Melish, John, Dixon, Brad, Adolphe, Allen, Kovesdy, Csaba, Beddhu, Srinivasan, Solomon, Richard, Fernando, Ronald, Levin, Ellis, Thakar, Charuhas, Robey, Brooks, Goldfarb, David, Fried, Linda, Maddukuri, Geetha, Thomson, Stephen, Annand, Andrew, Kronfli, Saeed, Kalirao, Paramjit, Schmidt, Rebecca, Dahl, Neera, Blumenthal, Samuel, Weinstein, Debra, Ostergaard, Ove, Weinstein, Talia, Ono, Yasuhiro, Yalcin, Murat, Karim, Shahana, Heerspink, Hiddo J L, Parving, Hans-Henrik, Andress, Dennis L, Correa-Rotter, Ricardo, Hou, Fan-Fan, Kitzman, Dalane W, Kohan, Donald, Makino, Hirofumi, McMurray, John J V, Melnick, Joel Z, Miller, Michael G, Pergola, Pablo E, Perkovic, Vlado, Yi, Tingting, Wigderson, Melissa, and de Zeeuw, Dick

Published
2019
Full Text
View/download PDF

44. PROBLEMS

Author

Stanescu, Florin, Trevi˜no, Enrique, Furdui, Ovidiu, Sîntămărian, Alina, Băetu, Ioan, Mero, Su Pernu, Bataille, Michel, Harmon, Luke, Oman, Greg, Marinescu, Dan Stefan, Giugiuc, Leonard, Jager, Tom, Mihăilă, Ioana, Bojaxhiu, Elton, Hysnelaj, Enkel, Delacroix, Eugène, Herschkorn, Stephen J., DEMIR, Baris Burcin, Gatesman, Kyle, Stoica, George, and Chapman, Robin

Published
2019

45. 12075

Author

Stoica, George and John, Saint

Published
2018

47. PROBLEMS

Author

Plaza, Ángel, Bataille, Michel, Kim, Sung Soo, Stanescu, Florin, Băetu, Ioan, Gaitanas, Konstantinos, Stoica, George, Gökçe, Lokman, Chapman, Robin, Tetiva, Marian, Singer, Nicholas, Gheorghe, Oniciuc, Schilling, Kenneth, DiMuro, Joseph, and Sharma, Rajesh

Published
2018

49. PROBLEMS

Author

Băetu, Ioan, Stoica, George, Sorel, Julien, Kominers, Scott Duke, Kim, Sung Soo, Gökçe, Lokman, Bataille, Michel, Caragiu, Mihai, Bencze, Mihàly, Merca, Mircea, and Nita, Valerian

Published
2018

Catalog

Books, media, physical & digital resources
See catalog results