End-to-end learning
End-to-end learning is a training approach that jointly learns a complete model or connected pipeline to map inputs to outputs under a shared objective.
Sutskever's List
End-to-end training is a training approach that learns a complete mapping from raw inputs to outputs without separately engineered intermediate representations.
- How it is used
- Uses learned mappings from raw inputs to outputs to replace separately engineered intermediate representations.
- How deep it goes
- Explains the approach conceptually through a landmark result rather than detailing architecture, optimization, or training mechanics.
- Examples
- Uses AlexNet’s 2012 ImageNet and ILSVRC victory as its central example.
- What you can do after
- Evaluate why end-to-end neural training became a turning point in computer vision.
Optimization Algorithms: AI techniques for design, planning, and control problems
A learning approach that trains a model to map inputs directly to desired outputs with minimal separately engineered intermediate stages.
- How it is used
- Directs machine learning to formulate solutions for combinatorial optimization problems from their input instances.
- How deep it goes
- Defines direct formulation and contrasts two alternatives, but stops short of detailing training procedures or implementation.
- Examples
- Uses pointer networks trained and validated on differently sized Euclidean planar symmetric traveling-salesperson instances.
- What you can do after
- Evaluate direct solution formulation against learned algorithm configuration and repeatedly model-guided optimization.
Related concepts
- Deep Speech 2used by · Deep Speech 2 is a large-scale neural speech-recognition system designed for end-to-end automatic speech recognition.
- objective functionuses · An objective function assigns values to candidate solutions, predictions, or parameter settings according to a criterion to be minimized or maximized.
- Retrieveruses · A retriever is a software component that searches or queries an information source and returns items relevant to a query for use by downstream processes.
- modularitycontrasts with · Modularity is the property of a system being organized into separable components with distinct responsibilities and defined interactions.
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