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 271–280 of 639 papers

TitleStatusHype
An Improved Non-monotonic Transition System for Dependency Parsing—0
A Fully Convolutional Neural Network based Structured Prediction Approach Towards the Retinal Vessel Segmentation—0
Active Learning for Structured Prediction from Partially Labeled Data—0
Predicting gait events from tibial acceleration in rearfoot running: a structured machine learning approach—0
End-to-End Learning for Structured Prediction Energy Networks—0
Book Review: Linguistic Structure Prediction by Noah A. Smith—0
Emotion-Conditioned Text Generation through Automatic Prompt Optimization—0
Blending Learning and Inference in Structured Prediction—0
A New Smooth Approximation to the Zero One Loss with a Probabilistic Interpretation—0
Efficient Structured Surrogate Loss and Regularization in Structured Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified