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Jang, Jun-Gi
3169  Ergebnisse:
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1

Accurate bundle matching and generation via multitask learn..:

Jeon, Hyunsik ; Jang, Jun-Gi ; Kim, Taehun..
PLOS ONE.  18 (2023)  3 - p. e0280630 , 2023
Link: https://doi.org/10.1371/..
 
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2

Falcon: lightweight and accurate convolution based on depth..:

Jang, Jun-Gi ; Quan, Chun ; Lee, Hyun Dong.
Knowledge and Information Systems.  65 (2023)  5 - p. 2225-2249 , 2023
Link: https://doi.org/10.1007/..
 
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3

Fast and Accurate Dual-Way Streaming PARAFAC2 for Irregular..:

, In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,
Jang, Jun-Gi ; Lee, Jeongyoung ; Park, Yong-chan. - p. 879-890 , 2023
Link: https://dl.acm.org/doi/1..
 
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4

Accurate Open-Set Recognition for Memory Workload:

Jang, Jun-Gi ; Shim, Sooyeon ; Egay, Vladimir...
ACM Transactions on Knowledge Discovery from Data.  17 (2023)  9 - p. 1-14 , 2023
Link: https://doi.org/10.1145/..
 
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5

Static and Streaming Tucker Decomposition for Dense Tensors:

Jang, Jun-Gi ; Kang, U
ACM Transactions on Knowledge Discovery from Data.  17 (2023)  5 - p. 1-34 , 2023
Link: https://doi.org/10.1145/..
 
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6

Fast and accurate interpretation of workload classification..:

Shim, Sooyeon ; Kim, Doyeon ; Jang, Jun-Gi...
PLOS ONE.  18 (2023)  3 - p. e0282595 , 2023
Link: https://doi.org/10.1371/..
 
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7

DPar2: Fast and Scalable PARAFAC2 Decomposition for Irregul..:

, In: 2022 IEEE 38th International Conference on Data Engineering (ICDE),
Jang, Jun-Gi ; Kang, U - p. 2454-2467 , 2022
Link: https://doi.org/10.1109/..
 
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8

Accurate PARAFAC2 Decomposition for Temporal Irregular Tens..:

, In: 2022 IEEE International Conference on Big Data (Big Data),
Jang, Jun-Gi ; Lee, Jeongyoung ; Park, Jiwon. - p. 982-991 , 2022
Link: https://doi.org/10.1109/..
 
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9

Large-scale tucker Tensor factorization for sparse and accu..:

Jang, Jun-Gi ; Park, Moonjeong ; Lee, Jongwuk.
The Journal of Supercomputing.  78 (2022)  16 - p. 17992-18022 , 2022
Link: https://doi.org/10.1007/..
 
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10

Finding Key Structures in MMORPG Graph with Hierarchical Gr..:

Jang, Jun-Gi ; Park, Chaeheum ; Jang, Changwon..
ACM Transactions on Knowledge Discovery from Data.  16 (2022)  6 - p. 1-21 , 2022
Link: https://doi.org/10.1145/..
 
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11

Fast and Accurate Partial Fourier Transform for Time Series..:

, In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining,
Park, Yong-chan ; Jang, Jun-Gi ; Kang, U - p. 1309-1318 , 2021
Link: https://dl.acm.org/doi/1..
 
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12

Time-aware tensor decomposition for sparse tensors:

Ahn, Dawon ; Jang, Jun-Gi ; Kang, U
Machine Learning.  111 (2021)  4 - p. 1409-1430 , 2021
Link: https://doi.org/10.1007/..
 
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13

Fast and Memory-Efficient Tucker Decomposition for Answerin..:

, In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining,
Jang, Jun-Gi ; Kang, U - p. 725-735 , 2021
Link: https://dl.acm.org/doi/1..
 
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14

D-Tucker: Fast and Memory-Efficient Tucker Decomposition fo..:

, In: 2020 IEEE 36th International Conference on Data Engineering (ICDE),
Jang, Jun-Gi ; Kang, U - p. 1850-1853 , 2020
Link: https://doi.org/10.1109/..
 
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15

S3CMTF: Fast, accurate, and scalable method for incomplete ..:

Choi, Dongjin ; Jang, Jun-Gi ; Kang, U.
PLOS ONE.  14 (2019)  6 - p. e0217316 , 2019
Link: https://doi.org/10.1371/..
 
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