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AI@Google - Artificial general intelligence - Arxiv Doc - Clustering - Combinatorial generalization - Curse of dimensionality - Graph neural networks - Information retrieval - Metrics - Multi-label classification - Multi-task learning - NLP - NN / Symbolic AI hybridation - Relational inductive biases - TODO-READ! - Wikipedia -

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9 Documents (Liste longue)

On the Surprising Behavior of Distance Metrics in High Dimensional Space (Aggarwal 2001)

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2024-03-03 A propos

Information Retrieval as Statistical Translation (Adam Berger , John Lafferty, 1999)

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2019-04-18 A propos

Wikify!: linking documents to encyclopedic knowledge (2007)

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2019-04-16 A propos

A SIMPLE ALGORITHM FOR IDENTIFYING ABBREVIATION DEFINITIONS IN BIOMEDICAL TEXT

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2019-04-03 A propos

[1806.01261] Relational inductive biases, deep learning, and graph networks

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2018-06-13 A propos

ML-knn: A lazy learning approach to multi-label learning (2007)

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a lazy learning approach derived from the traditional [k-nearest neighbors algorithm](tag:k_nearest_neighbors_algorithm)

> for each unseen instance, its K nearest neighbors in the training set are firstly identified. After that, based on statistical information gained from the label sets of these neighboring instances, i.e. the number of neighboring instances belonging to each possible class, [Maximum a posteriori (MAP)](tag:maximum_a_posteriori_estimation) principle is utilized to determine the label set for the unseen instance.

Implemented in [scikit-multilearn](http://scikit.ml/api/skmultilearn.adapt.mlknn.html), in [java](https://github.com/lefman/mulan-extended/blob/master/mulan/src/mulan/classifier/lazy/MLkNN.java)

> the first lazy approach proposed specifically for multi-label classification. This is also a binary relevance approach which considers each label independently as a binary classification problem. Instead of a standard k-NN method, however, MLkNN uses the maximum a-posteriori (MAP) (Kelleher et al., 2015) approach combined with k-NN. [src](https://pdfs.semanticscholar.org/af9b/33da37d290c063cd826ab5923d96892a9767.pdf)

2018-03-18 A propos

[1103.0398] Natural Language Processing (almost) from Scratch

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2018-01-17 A propos

Convolutional Neural Networks for Sentence Classification (2014)

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2017-11-07 A propos

Indexing by Latent Semantic Analysis - Deerwester et al. (1990)

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2017-07-18 A propos

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sl:creationDate : 2017-11-21
sl:creationTime : 2017-11-21T00:51:29Z
rdf:type : sl:Tag
skos:prefLabel : Frequently cited paper