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

Showing 531540 of 639 papers

TitleStatusHype
Object Localization based on Structural SVM using Privileged Information0
Structure Regularization for Structured Prediction: Theories and Experiments0
Submodular meets Structured: Finding Diverse Subsets in Exponentially-Large Structured Item Sets0
Conditional Random Field Autoencoders for Unsupervised Structured PredictionCode0
Constructing Information Networks Using One Single Model0
Prune-and-Score: Learning for Greedy Coreference Resolution0
Tight Error Bounds for Structured Prediction0
Metric Learning for Temporal Sequence Alignment0
Marginal Structured SVM with Hidden Variables0
A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Training Structural SVMs with a Costly max-Oracle0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified