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目录
1 概述篇 ······································································································ 1
1.1 机器学习的概念 ·············································································· 1
1.2 机器学习的发展历史 ········································································ 1
2 技术篇 ······································································································ 2
2.1 机器学习算法分类 ······································································· 2
2.2 机器学习的经典代表算法 ······························································ 2
2.3 生成对抗网络及对抗机器学习 ························································ 3
2.3.1 生成对抗网络 ······································································· 3
2.3.2 对抗机器学习 ······································································· 4
2.4 自动机器学习 ············································································· 4
2.4.1 AutoML ··············································································· 4
2.4.2 ATMSeer ············································································· 5
2.5 可解释性机器学习 ······································································· 6
2.6 在线学习 ··················································································· 6
2.7 BERT ························································································ 7
2.8 卷积与图卷积 ············································································· 8
2.8.1 卷积 ··················································································· 8
2.8.2 图卷积 ················································································ 9
2.9 隐私保护 ·················································································· 10
3 深度学习篇······························································································· 11
3.1 卷积神经网络 ············································································ 12
3.2 AutoEncoder ·············································································· 12
3.3 循环神经网络 RNN ····································································· 13
3.4 网络表示学习与图神经网络 GNN ··················································· 13
3.5 增强学习 ·················································································· 14
3.6 生成对抗网络 ············································································ 14
3.7 老虎机 ····················································································· 15
3.8 图神经网络 ··············································································· 15
3.9 深度学习近期重要进展 ································································ 16
3.9.1 2018 年三大进展 ··································································· 16
3.9.2 2019 年三大进展 ··································································· 17
4 论文解读篇······························································································· 18
5 人才篇 ····································································································· 21
5.1 学者情况概览 ············································································ 21
5.2 代表性学者简介 ········································································· 23
5.2.1 国际代表性学者 ··································································· 24
5.2.2 国内代表性学者 ··································································· 24
5.3 NeurIPS 十年高引学者 ································································· 26
6 应用篇 ····································································································· 30
6.1 行业应用 ·················································································· 30
6.1.1 金融行业应用 ······································································ 30
6.1.2 自动驾驶 ············································································ 31
6.1.3 健康和医疗 ········································································· 32
6.1.4 零售业 ··············································································· 34
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