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

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Showing 291–300 of 639 papers

TitleStatusHype
Latent Structured Active Learning—0
Latent Structures for Coreference Resolution—0
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation—0
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations—0
Learning Adaptive Value of Information for Structured Prediction—0
Improving Joint Training of Inference Networks and Structured Prediction Energy Networks—0
A Survey of Active Learning for Natural Language Processing—0
Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing—0
A Structured Approach to Predicting Image Enhancement Parameters—0
Learning Discriminators as Energy Networks in Adversarial Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified