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Stream-Flow Forecasting of Small Rivers Based on LSTM
Stream-flow forecasting for small rivers has always been of great import...
01/16/2020 ∙ by Youchuan Hu, et al. ∙
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Multi-Kernel Filtering: An Extension of Bilateral Filtering Using Image Context
Bilateral filtering is one of the most classical denoising filters. Howe...
08/17/2019 ∙ by Feihong Liu, et al. ∙
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DeepBundle: Fiber Bundle Parcellation with Graph Convolution Neural Networks
Parcellation of whole-brain tractography streamlines is an important ste...
06/07/2019 ∙ by Feihong Liu, et al. ∙
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Aggregating E-commerce Search Results from Heterogeneous Sources via Hierarchical Reinforcement Learning
In this paper, we investigate the task of aggregating search results fro...
02/24/2019 ∙ by Ryuichi Takanobu, et al. ∙
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Relation Mention Extraction from Noisy Data with Hierarchical Reinforcement Learning
In this paper we address a task of relation mention extraction from nois...
11/03/2018 ∙ by Jun Feng, et al. ∙
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Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning
Ranking is a fundamental and widely studied problem in scenarios such as...
09/17/2018 ∙ by Jun Feng, et al. ∙
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Reinforcement Learning for Relation Classification from Noisy Data
Existing relation classification methods that rely on distant supervisio...
08/24/2018 ∙ by Jun Feng, et al. ∙
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Software Engineering Solutions To Support Vertical Transportation
In this paper we introduce the core results of the project on visualisat...
12/13/2017 ∙ by Alber J. Christianto, et al. ∙
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Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks
Click prediction is one of the fundamental problems in sponsored search....
04/23/2014 ∙ by Yuyu Zhang, et al. ∙
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