재정 지원 요구사항을 통해 공개된 자료 - Assefaw Gebremedhin자세히 알아보기
제공된 곳이 없음: 7
An adaptive machine learning framework for behind-the-meter load/PV disaggregation
R Saeedi, SK Sadanandan, AK Srivastava, KL Davies, AH Gebremedhin
IEEE Transactions on Industrial Informatics 17 (10), 7060-7069, 2021
재정 지원 요구사항 정책: US Department of Energy
Synthetic sensor data generation for health applications: A supervised deep learning approach
S Norgaard, R Saeedi, K Sasani, AH Gebremedhin
2018 40th Annual International Conference of the IEEE Engineering in …, 2018
재정 지원 요구사항 정책: US National Science Foundation
Personalized human activity recognition using wearables: A manifold learning-based knowledge transfer
R Saeedi, K Sasani, S Norgaard, AH Gebremedhin
2018 40th Annual International Conference of the IEEE Engineering in …, 2018
재정 지원 요구사항 정책: US National Science Foundation
Multi-sensor time-series classification for activity tracking under variable length
S Norgaard, R Saeedi, AH Gebremedhin
IEEE sensors journal 20 (5), 2701-2709, 2019
재정 지원 요구사항 정책: US National Science Foundation
Evaluation of native and transfer students' success in a computer science course
H Catanese, C Hauser, AH Gebremedhin
ACM Inroads 9 (2), 53-57, 2018
재정 지원 요구사항 정책: US National Science Foundation
RMACXX: An Efficient High-Level C++ Interface over MPI-3 RMA
S Ghosh, Y Guo, P Balaji, AH Gebremedhin
2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet …, 2021
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy
Paradigms for Effective Parallelization of Inherently Sequential Graph Algorithms on Multi-Core Architectures
A Gebremedhin, M Patwary, F Manne
Handbook of Research on Methodologies and Applications of Supercomputing, 74-95, 2021
재정 지원 요구사항 정책: US National Science Foundation
제공된 곳이 있음: 41
Distributed louvain algorithm for graph community detection
S Ghosh, M Halappanavar, A Tumeo, A Kalyanaraman, H Lu, ...
2018 IEEE international parallel and distributed processing symposium (IPDPS …, 2018
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy
Parallel maximum clique algorithms with applications to network analysis
RA Rossi, DF Gleich, AH Gebremedhin
SIAM Journal on Scientific Computing 37 (5), C589-C616, 2015
재정 지원 요구사항 정책: US Department of Energy
Efficient computation of sparse Hessians using coloring and automatic differentiation
AH Gebremedhin, A Tarafdar, A Pothen, A Walther
INFORMS Journal on Computing 21 (2), 209-223, 2009
재정 지원 요구사항 정책: German Research Foundation
A framework for scalable greedy coloring on distributed-memory parallel computers
D Bozdağ, AH Gebremedhin, F Manne, EG Boman, UV Catalyurek
Journal of Parallel and Distributed Computing 68 (4), 515-535, 2008
재정 지원 요구사항 정책: US National Institutes of Health
Fast algorithms for the maximum clique problem on massive graphs with applications to overlapping community detection
B Pattabiraman, MMA Patwary, AH Gebremedhin, W Liao, A Choudhary
Internet Mathematics 11 (4-5), 421-448, 2015
재정 지원 요구사항 정책: US Department of Energy
MPC-based decentralized voltage control in power distribution systems with EV and PV coordination
L Wang, A Dubey, AH Gebremedhin, AK Srivastava, N Schulz
IEEE Transactions on Smart Grid 13 (4), 2908-2919, 2022
재정 지원 요구사항 정책: US Department of Energy
RepeatAnalyzer: a tool for analysing and managing short-sequence repeat data
HN Catanese, KA Brayton, AH Gebremedhin
BMC genomics 17, 1-13, 2016
재정 지원 요구사항 정책: US National Science Foundation
An introduction to algorithmic differentiation
AH Gebremedhin, A Walther
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 10 (1 …, 2020
재정 지원 요구사항 정책: US National Science Foundation
Algorithms for balanced graph colorings with applications in parallel computing
H Lu, M Halappanavar, D Chavarria-Miranda, AH Gebremedhin, ...
IEEE Transactions on Parallel and Distributed Systems 28 (5), 1240-1256, 2016
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy
Balanced coloring for parallel computing applications
H Lu, M Halappanavar, D Chavarría-Miranda, A Gebremedhin, ...
2015 IEEE International Parallel and Distributed Processing Symposium, 7-16, 2015
재정 지원 요구사항 정책: US Department of Energy
A closed-loop deep learning architecture for robust activity recognition using wearable sensors
R Saeedi, S Norgaard, AH Gebremedhin
2017 IEEE International Conference on Big Data (Big Data), 473-479, 2017
재정 지원 요구사항 정책: US National Science Foundation
Transfer learning algorithms for autonomous reconfiguration of wearable systems
R Saeedi, H Ghasemzadeh, AH Gebremedhin
2016 IEEE International Conference on Big Data (Big Data), 563-569, 2016
재정 지원 요구사항 정책: US National Science Foundation
miniVite: A graph analytics benchmarking tool for massively parallel systems
S Ghosh, M Halappanavar, A Tumeo, A Kalyanaraman, AH Gebremedhin
2018 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High …, 2018
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy
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