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 611–620 of 639 papers

TitleStatusHype
Gradient-based Inference for Networks with Output Constraints—0
Graph-Based Lexicon Expansion with Sparsity-Inducing Penalties—0
Graph-Based Posterior Regularization for Semi-Supervised Structured Prediction—0
Gray-box inference for structured Gaussian process models—0
Grounded Video Situation Recognition—0
Hands-on Learning to Search for Structured Prediction—0
HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports—0
HC-Search for Structured Prediction in Computer Vision—0
Helix: Accelerating Human-in-the-loop Machine Learning—0
Hierarchical Poset Decoding for Compositional Generalization in Language—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified