Feature selection, L 1 vs. L 2 regularization, and rotational invariance
The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.
this paper
works it cites
works citing it
node size = global citations · hover for the full title
Citation edge evidence
- Recurrent Convolutional Neural Networks for Text Classification→Feature selection, L 1 vs. L 2 regularization, and rotational invarianceLegacy edge — source detail unavailable
- Describing objects by their attributes→Feature selection, L 1 vs. L 2 regularization, and rotational invarianceLegacy edge — source detail unavailable
- Feature selection, L 1 vs. L 2 regularization, and rotational invariance→Statistical Learning TheoryLegacy edge — source detail unavailable
- Feature selection, L 1 vs. L 2 regularization, and rotational invariance→Training Products of Experts by Minimizing Contrastive DivergenceLegacy edge — source detail unavailable
- Feature selection, L 1 vs. L 2 regularization, and rotational invariance→Selection of relevant features and examples in machine learningLegacy edge — source detail unavailable
- Feature selection, L 1 vs. L 2 regularization, and rotational invariance→Pattern Classification (2nd ed.)Legacy edge — source detail unavailable
- Feature selection, L 1 vs. L 2 regularization, and rotational invariance→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Selection of relevant features and examples in machine learning→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Recurrent Convolutional Neural Networks for Text Classification | 2015 | 2,314 |
| Describing objects by their attributes | 2009 | 1,936 |
Links
Topics
| Machine Learning and Algorithms | Computer Science |
| Neural Networks and Applications | Computer Science |
| Face and Expression Recognition | Computer Science |
Is this record sound?
complete
Nothing in this record contradicts itself and no field we check is missing.
- supports1 author record(s) attached.
- supports29 reference(s) recorded.
- neutralThe DOI carries no year to check against.
- supportsA title is present.
Provenance
sha256 b3024609427ad450…