Matheus Ribeiro Furtado de Mendonça

Idiomas

Produções bibliográficas

• MENDONÇA, MATHEUS R. F. ; BARRETO, ANDRÉ M. S. ; ZIVIANI, ARTUR . Efficient information diffusion in time-varying graphs through deep reinforcement learning. WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS , v. 25, p. 2535-2560, 2022.

• Dayan, Ittai Roth, Holger R. ZHONG, AOXIAO Harouni, Ahmed GENTILI, AMILCARE ABIDIN, ANAS Z. LIU, ANDREW COSTA, ANTHONY BEARDSWORTH WOOD, BRADFORD J. TSAI, CHIEN-SUNG WANG, CHIH-HUNG HSU, CHUN-NAN LEE, C. K. RUAN, PEIYING Xu, Daguang WU, DUFAN HUANG, EDDIE KITAMURA, FELIPE CAMPOS LACEY, GRIFFIN DE ANTÔNIO CORRADI, GUSTAVO CÉSAR NINO, GUSTAVO SHIN, HAO-HSIN OBINATA, HIROFUMI REN, HUI CRANE, JASON C. , et al. Tetreault, Jesse GUAN, JIAHUI GARRETT, JOHN W. KAGGIE, JOSHUA D. PARK, JUNG GIL DREYER, KEITH JULURU, KRISHNA KERSTEN, KRISTOPHER ROCKENBACH, MARCIO ALOISIO BEZERRA CAVALCANTI LINGURARU, MARIUS GEORGE HAIDER, MASOOM A. ABDELMASEEH, MEENA RIEKE, NICOLA DAMASCENO, PABLO F. E SILVA, PEDRO MARIO CRUZ WANG, POCHUAN XU, SHENG KAWANO, SHUICHI SRISWASDI, SIRA PARK, SOO YOUNG GRIST, THOMAS M. Buch, Varun JANTARABENJAKUL, WATSAMON WANG, WEICHUNG TAK, WON YOUNG LI, XIANG LIN, XIHONG KWON, YOUNG JOON QURAINI, ABOOD FENG, ANDREW PRIEST, ANDREW N. TURKBEY, BARIS GLICKSBERG, BENJAMIN BIZZO, BERNARDO KIM, BYUNG SEOK TOR-DÍEZ, CARLOS LEE, CHIA-CHENG HSU, CHIA-JUNG LIN, CHIN LAI, CHIU-LING HESS, CHRISTOPHER P. Compas, Colin BHATIA, DEEPEKSHA OERMANN, ERIC K. Leibovitz, Evan SASAKI, HISASHI MORI, HITOSHI YANG, ISAAC SOHN, JAE HO MURTHY, KRISHNA NAND KESHAVA FU, LI-CHEN DE MENDONÇA, MATHEUS RIBEIRO FURTADO FRALICK, MIKE KANG, MIN KYU ADIL, MOHAMMAD GANGAI, NATALIE VATEEKUL, PEERAPON ELNAJJAR, PIERRE HICKMAN, SARAH MAJUMDAR, SHARMILA MCLEOD, SHELLEY L. REED, SHERIDAN GRÄF, STEFAN HARMON, STEPHANIE KODAMA, TATSUYA PUTHANAKIT, THANYAWEE MAZZULLI, TONY DE LAVOR, VITOR LIMA RAKVONGTHAI, YOTHIN LEE, YU RIM Wen, Yuhong GILBERT, FIONA J. FLORES, MONA G. LI, QUANZHENG ; Federated learning for predicting clinical outcomes in patients with COVID-19. NATURE MEDICINE (ONLINE) , v. 27, p. 1735, 2021.

• BARROS, C. D. T. ; MENDONÇA, M. R. F. ; VIEIRA, A. B. ; ZIVIANI, A. . A Survey on Embedding Dynamic Graphs. ACM COMPUTING SURVEYS , v. 55, p. 10-47, 2021.

• MENDONCA, MATHEUS RIBEIRO FURTADO DE ; BARRETO, ANDRE MOTTA SALLES ; ZIVIANI, ARTUR . Approximating Network Centrality Measures Using Node Embedding and Machine Learning. IEEE Transactions on Network Science and Engineering , v. 8, p. 1-1, 2020.

• MENDONÇA, M. R. F. ; ZIVIANI, A. ; BARRETO, A. M. S. . Graph-Based Skill Acquisition For Reinforcement Learning. ACM COMPUTING SURVEYS , v. 52, p. 1-26, 2019.

• MENDONÇA, MATHEUS R. F. ; ZIVIANI, ARTUR . Network-Based Procedural Story Generation. COMPUTERS IN ENTERTAINMENT , v. 16, p. 1-18, 2018.

• MENDONÇA, MATHEUS R.F. ; BERNARDINO, HEDER S. ; NETO, RAUL FONSECA . Reinforcement learning with optimized reward function for stealth applications. ENTERTAINMENT COMPUTING , v. 25, p. 37-47, 2018.

• Roth, Holger R. Chang, Ken Singh, Praveer Neumark, Nir Li, Wenqi Gupta, Vikash Gupta, Sharut Qu, Liangqiong Ihsani, Alvin Bizzo, Bernardo C. Wen, Yuhong Buch, Varun Shah, Meesam Kitamura, Felipe Mendonça, Matheus Lavor, Vitor Harouni, Ahmed Compas, Colin Tetreault, Jesse Dogra, Prerna Cheng, Yan Erdal, Selnur White, Richard Hashemian, Behrooz Schultz, Thomas , et al. Zhang, Miao McCarthy, Adam Yun, B. Min Sharaf, Elshaimaa Hoebel, Katharina V. Patel, Jay B. Chen, Bryan Ko, Sean Leibovitz, Evan Pisano, Etta D. Coombs, Laura Xu, Daguang Dreyer, Keith J. Dayan, Ittai Naidu, Ram C. Flores, Mona Rubin, Daniel Kalpathy-Cramer, Jayashree ; Federated Learning for Breast Density Classification: A Real-World Implementation. Lecture Notes in Computer Science. 1ed.: Springer International Publishing, 2020, v. , p. 181-191.

• MENDONCA, MATHEUS ; ZIVIANI, ARTUR ; BARRETO, ANDRE . Laplacian using Abstract State Transition Graphs: A Framework for Skill Acquisition. In: 2019 8th Brazilian Conference on Intelligent Systems (BRACIS), 2019, Salvador. 2019 8th Brazilian Conference on Intelligent Systems (BRACIS), 2019. p. 263.

• MENDONÇA, M. R. F. ; ZIVIANI, A. ; BARRETO, A. M. S. . Abstract State Transition Graphs for Model-Based Reinforcement Learning. In: Brazilian Conference on Intelligent Systems, 2018, São Paulo. Procedings of the 7th Brazilian Conference on Intelligent Systems, 2018.

• MENDONCA, MATHEUS R.F. ; BERNARDINO, HEDER S. ; NETO, RAUL F. . Stealthy Path Planning Using Navigation Meshes. In: 2015 Brazilian Conference on Intelligent Systems (BRACIS), 2015, Natal. 2015 Brazilian Conference on Intelligent Systems (BRACIS), 2015. p. 31-36.

• MENDONCA, MATHEUS R. F. ; BERNARDINO, HEDER S. ; NETO, RAUL F. . Simulating Human Behavior in Fighting Games Using Reinforcement Learning and Artificial Neural Networks. In: 2015 14th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames), 2015, Piauí. 2015 14th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames), 2015. p. 152-32.

• HAUCK, J. V. S. ; MENDONÇA, M. R. F. ; SILVA, R. L. S. . Occlusion of virtual objects for augmented reality systems using Kinect. In: Workshop de Realidade Virtual e Aumentada (WRVA), 2014, Marília. XV WORKSHOP DE REALIDADE VIRTUAL E AUMENTADA, 2014. p. 83-87.

• Andrade, Guilherme ; MENDONÇA, M. R. F. ; Rocha, L.C ; SACHETTO, RAFAEL ; MADEIRA, D ; RAMOS, G . Escalonamento em Arquiteturas Heterogêneas: Um Estudo Comparativo. In: GPU Computing Developer Forum, 2012, Curitiba. XXXII Congresso da Sociedade Brasileira de Computação, 2012.

• MENDONÇA, M. R. F. ; ZIVIANI, A. ; BARRETO, A. M. S. . Laplacian using Abstract State Transition Graphs: A Framework for Skill Acquisition. 2019. (Apresentação de Trabalho/Congresso).

• MENDONÇA, M. R. F. ; ZIVIANI, A. ; BARRETO, A. M. S. . Abstract State Transition Graphs for Model-Based Reinforcement Learning. 2018. (Apresentação de Trabalho/Congresso).

• MENDONÇA, M. R. F. . Jogando ATARI com Aprendizado por Reforço Profundo. 2017. (Apresentação de Trabalho/Conferência ou palestra).

• MENDONÇA, M. R. F. ; BERNARDINO, H. S. ; FONSECA NETO, R. . Evolution of Reward Functions for Reinforcement Learning applied to Stealth Games. 2016. (Apresentação de Trabalho/Congresso).

• MENDONÇA, M. R. F. ; BERNARDINO, H. S. ; FONSECA NETO, R. . Stealthy path planning usign navigation meshes. 2015. (Apresentação de Trabalho/Congresso).

• MENDONÇA, M. R. F. ; BERNARDINO, H. S. ; FONSECA NETO, R. . Simulating Human Behavior in Fighting Games using Reinforcement Learning and Artificial Neural Networks. 2015. (Apresentação de Trabalho/Congresso).

• MENDONÇA, M. R. F. . Inteligência Artificial Aplicada A Jogos. 2014. (Apresentação de Trabalho/Conferência ou palestra).

• MENDONÇA, M. R. F. ; Rocha, L.C . Desenvolvimento e implementação de um algoritmo paralelo para o modelo de depressão alastrante. 2011. (Apresentação de Trabalho/Congresso).

• TAKAHASHI, M. S. ; MENDONÇA, M. R. F. ; PAN, I. ; PINETTI, R. Z. ; KITAMURA, F. C. . Regarding ?Serial Quantitative Chest CT Assessment of COVID-19: Deep-Learning Approach?. Radiology: Cardiothoracic Imaging, 2020 (Letter to the Editor).

Prêmios