文件名称:tpprl
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所属分类:
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- 上传时间:2019-04-09
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文件大小:533kb
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已下载:1次
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提 供 者:
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结合深度强化学习和时间点过程算法的实现,主要用python(In combination with deep reinforcement learning and implementation of time point process algorithm, Python is mainly used.)
相关搜索: 深度强化学习
(系统自动生成,下载前可以参看下载内容)
下载文件列表
文件名 | 大小 | 更新时间 |
---|---|---|
tpprl\.gitignore | 856 | 2019-01-12 |
tpprl\.idea\misc.xml | 272 | 2019-01-14 |
tpprl\.idea\modules.xml | 250 | 2019-01-14 |
tpprl\.idea\workspace.xml | 17284 | 2019-01-14 |
tpprl\analyze-broadcasting.py | 19150 | 2019-01-12 |
tpprl\analyze-spaced-repetition.py | 8262 | 2019-01-12 |
tpprl\broadcasting-analysis.csv | 150328 | 2019-01-12 |
tpprl\data\initial_difficulty.csv | 599 | 2019-01-12 |
tpprl\data\r_2.csv | 377 | 2019-01-12 |
tpprl\data\top_k.csv | 377 | 2019-01-12 |
tpprl\output-plots\algo-avg-rank.pdf | 98227 | 2019-01-12 |
tpprl\output-plots\algo-top-1.pdf | 98378 | 2019-01-12 |
tpprl\output-plots\item-difficulty.pdf | 98291 | 2019-01-12 |
tpprl\output-plots\recall-results-14-2.pdf | 63593 | 2019-01-12 |
tpprl\output-plots\reviews-every-day.pdf | 64076 | 2019-01-12 |
tpprl\plot-smart-broadcasting.py | 5111 | 2019-01-12 |
tpprl\README.md | 3301 | 2019-01-12 |
tpprl\sbatch\exp_run.py | 3783 | 2019-01-12 |
tpprl\sbatch\r_2_job.sh | 471 | 2019-01-12 |
tpprl\sbatch\top_k_job.sh | 497 | 2019-01-12 |
tpprl\tpprl\cells.py | 15870 | 2019-01-12 |
tpprl\tpprl\exp_broadcaster.py | 80062 | 2019-01-12 |
tpprl\tpprl\exp_sampler.py | 29856 | 2019-01-12 |
tpprl\tpprl\exp_teacher.py | 50962 | 2019-01-12 |
tpprl\tpprl\plot_utils.py | 3656 | 2019-01-12 |
tpprl\tpprl\read_data_utils.py | 6062 | 2019-01-12 |
tpprl\tpprl\utils.py | 2566 | 2019-01-12 |
tpprl\tpprl\__init__.py | 0 | 2019-01-12 |
tpprl\tpprl.iml | 338 | 2019-01-14 |
tpprl\train-broadcasting.py | 11038 | 2019-01-12 |
tpprl\train-teaching.py | 5556 | 2019-01-12 |
tpprl\.idea | 0 | 2019-01-14 |
tpprl\data | 0 | 2019-01-14 |
tpprl\output-plots | 0 | 2019-01-14 |
tpprl\sbatch | 0 | 2019-01-14 |
tpprl\tpprl | 0 | 2019-01-14 |
tpprl | 0 | 2019-01-14 |
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