列出的学习单元属于课程Computational Learning Theory and Beyond。您想访问所有课程内容吗？
Week 1
Welcome to the Course
文本
Pre-Course Survey
调查
1.1 Binary Classification
视频
1.1 Binary Classification
自我测试
Excursus 1: Feature Extraction with Neural Networks
视频
1.2 Training Sequences
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1.2 Training Sequences
自我测试
Excursus 2: Theory of Evolutionary Algorithms
视频
1.3 Hypothesis Space
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1.3 Hypothesis Space
自我测试
Excursus 3: Fair Clustering
视频
1.4 Informants and Successful Learning
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1.4 Informants and Succesful Learning
自我测试
Excursus 4: Game Theory, Segregation and Potential Functions
视频
2.1 Learnability of Hypothesis Spaces
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2.1 Learnability of Hypothesis Spaces
自我测试
Excursus 5: Submodular Maximisation
视频
Learning Material
文本
Homework Week 1
分级测试
Week 2
Welcome to Week 2
文本
2.2 LOCK Property and Storing Points
视频
2.2 LOCK Property and Storing Points
自我测试
Excursus 6: Learning from Positive Data - Overview
视频
2.3 An Iterative Learner for the Set of Halfspaces
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2.3 An Iterative Learner for the Set of Halfspaces
自我测试
Excursus 7: Learning from Positive Data - Additional Requirements
视频
2.4 Learning Success on the Set of Halfspaces
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2.4 Learning Success on the Set of Halfspaces
自我测试
Excursus 8: Embeddings
视频
2.5 Minibatch versus Batch Learners
视频
2.5 Minibatch versus Batch-Learners
自我测试
Excursus 9: Stable Matchings
视频
3.1 Consistency
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3.1 Consistency
自我测试
Excursus 10: Boolean Satisfiability (SAT)
视频
Learning Material
文本
Homework Week 2
分级测试
Excursus 11: Inductive Inference
视频