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 411–420 of 639 papers

TitleStatusHype
Learning Stochastic Feedforward Neural Networks—0
Learning Structured Perceptrons for Coreference Resolution with Latent Antecedents and Non-local Features—0
Learning Structured Predictors from Bandit Feedback for Interactive NLP—0
Linear-Time Modeling of Linguistic Structure: An Order-Theoretic Perspective—0
Learning to generalize to new compositions in image understanding—0
Learning to Jointly Predict Ellipsis and Comparison Structures—0
Learning to Prune: Exploring the Frontier of Fast and Accurate Parsing—0
Learning to Search Better Than Your Teacher—0
Learning to Search in Branch and Bound Algorithms—0
Learning to Search on Manifolds for 3D Pose Estimation of Articulated Objects—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified