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 501–510 of 639 papers

TitleStatusHype
Transferring Coreference Resolvers with Posterior Regularization—0
A Neural Probabilistic Structured-Prediction Model for Transition-Based Dependency Parsing—0
Distributed Training of Structured SVM—0
Deeply Learning the Messages in Message Passing Inference—0
Semidefinite and Spectral Relaxations for Multi-Label Classification—0
Lisbon: Evaluating TurboSemanticParser on Multiple Languages and Out-of-Domain Data—0
Discovering Hypernymy Relations using Text Layout—0
Second-Order Constrained Parametric Proposals and Sequential Search-Based Structured Prediction for Semantic Segmentation in RGB-D Images—0
Active Learning for Structured Probabilistic Models With Histogram Approximation—0
HC-Search for Structured Prediction in Computer Vision—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified