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# Data Summarization Edit

7 papers with code · Miscellaneous

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# apricot: Submodular selection for data summarization in Python

8 Jun 2019jmschrei/apricot

This paper presents an explanation of submodular selection, an overview of the features in apricot, and an application to several data sets.

270

# Fast and Accurate Least-Mean-Squares Solvers

Least-mean squares (LMS) solvers such as Linear / Ridge / Lasso-Regression, SVD and Elastic-Net not only solve fundamental machine learning problems, but are also the building blocks in a variety of other methods, such as decision trees and matrix factorizations.

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# Soft-Label Dataset Distillation and Text Dataset Distillation

6 Oct 2019ilia10000/dataset-distillation

We propose to simultaneously distill both images and their labels, thus assigning each synthetic sample a `soft' label (a distribution of labels).

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# Fair k-Center Clustering for Data Summarization

24 Jan 2019matthklein/fair_k_center_clustering

In data summarization we want to choose $k$ prototypes in order to summarize a data set.

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# Fair and Diverse DPP-based Data Summarization

Sampling methods that choose a subset of the data proportional to its diversity in the feature space are popular for data summarization.

3

# Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer Vision

In our algorithm, at each iteration, the maximum information from the structure of the data is captured by one selected sample, and the captured information is neglected in the next iterations by projection on the null-space of previously selected samples.

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# A Mixed Hierarchical Attention based Encoder-Decoder Approach for Standard Table Summarization

Structured data summarization involves generation of natural language summaries from structured input data.

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