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Takumi Uchida

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2020 – today

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2024
[j1]
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  - journals/access/IshibashiU24
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  - https://dblp.org/rec/journals/access/IshibashiU24
Keisuke Ishibashi, Takumi Uchida:
Estimating Latent Traffic Demand From QoS Degradation Using a Time Series Causal Inference Approach. IEEE Access 12: 139346-139357 (2024)
2023
[c5]
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  - conf/teletraffic/IshibashiU23
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Keisuke Ishibashi, Takumi Uchida:
Estimating Traffic Latent Due to QoS Deterioration: A Time-Series Causal Inference Approach. ITC 2023: 1-6
2022
[c4]
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  - conf/kes/UchidaY22
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Takumi Uchida, Kenichi Yoshida:
Concept Drift in Japanese COVID-19 Infection Data. KES 2022: 380-387
2020
[c3]
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  - conf/compsac/UchidaIF20
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Takumi Uchida, Keisuke Ishibashi, Kensuke Fukuda:
Routing and Capacity Optimization Based on Estimated Latent OD Traffic Demand. COMPSAC 2020: 1169-1175

2010 – 2019

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2018
[c2]
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  - conf/pkdd/NakagawaUA18
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Kei Nakagawa, Takumi Uchida, Tomohisa Aoshima:
Deep Factor Model - Explaining Deep Learning Decisions for Forecasting Stock Returns with Layer-Wise Relevance Propagation. MIDAS/PAP@PKDD/ECML 2018: 37-50
2014
[c1]
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Takumi Uchida, Koken Ozaki, Kenichi Yoshida:
Toward a Faithful Bidding of Web Advertisement. HCI (18) 2014: 112-118

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