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 461–470 of 639 papers

TitleStatusHype
Active Learning for Structured Prediction from Partially Labeled Data—0
Active Learning for Structured Probabilistic Models With Histogram Approximation—0
Active Learning in Video Tracking—0
Active learning with version spaces for object detection—0
A Discriminative Graph-Based Parser for the Abstract Meaning Representation—0
Adversarial Structured Prediction for Multivariate Measures—0
A Fenchel-Young Loss Approach to Data-Driven Inverse Optimization—0
A Fully Convolutional Neural Network based Structured Prediction Approach Towards the Retinal Vessel Segmentation—0
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings—0
A General-Purpose Algorithm for Constrained Sequential Inference—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified