SOTAVerified

Structured Prediction

Structured Prediction is an area of machine learning focusing on representations of spaces with combinatorial structure, and algorithms for inference and parameter estimation over these structures. Core methods include both tractable exact approaches like dynamic programming and spanning tree algorithms as well as heuristic techniques such as linear programming relaxations and greedy search.

Source: Torch-Struct: Deep Structured Prediction Library

Papers

Showing 141150 of 639 papers

TitleStatusHype
A Unified Framework for Structured Prediction: From Theory to Practice0
A Music Classification Model based on Metric Learning and Feature Extraction from MP3 Audio Files0
A Consistent Regularization Approach for Structured Prediction0
Document Context Neural Machine Translation with Memory Networks0
"A Tale of Two Movements": Identifying and Comparing Perspectives in #BlackLivesMatter and #BlueLivesMatter Movements-related Tweets using Weakly Supervised Graph-based Structured Prediction0
A Survey of Active Learning for Natural Language Processing0
DeepSPIN: Deep Structured Prediction for Natural Language Processing0
A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Training Structural SVMs with a Costly max-Oracle0
Distributionally Robust Graphical Models0
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified