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Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices
In real-world machine learning applications, data subsets correspond to ...
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SysML: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
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Cross-Modal Data Programming Enables Rapid Medical Machine Learning
Labeling training datasets has become a key barrier to building medical ...
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Learning Dependency Structures for Weak Supervision Models
Labeling training data is a key bottleneck in the modern machine learnin...
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Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale
Labeling training data is one of the most costly bottlenecks in developi...
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Training Complex Models with Multi-Task Weak Supervision
As machine learning models continue to increase in complexity, collectin...
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Snorkel: Rapid Training Data Creation with Weak Supervision
Labeling training data is increasingly the largest bottleneck in deployi...
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Learning the Structure of Generative Models without Labeled Data
Curating labeled training data has become the primary bottleneck in mach...
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Data Programming: Creating Large Training Sets, Quickly
Large labeled training sets are the critical building blocks of supervis...
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