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 361–370 of 639 papers

TitleStatusHype
Sequence Classification with Neural Conditional Random Fields—0
Sequence Segmentation Using Joint RNN and Structured Prediction Models—0
Set-to-Sequence Methods in Machine Learning: a Review—0
SHARP: Search-Based Adversarial Attack for Structured Prediction—0
SHEF-MIME: Word-level Quality Estimation Using Imitation Learning—0
Sidestepping Intractable Inference with Structured Ensemble Cascades—0
Sigma Flows for Image and Data Labeling and Learning Structured Prediction—0
Simultaneous Twin Kernel Learning using Polynomial Transformations for Structured Prediction—0
Quantum Algorithms for Structured Prediction—0
Softmax Q-Distribution Estimation for Structured Prediction: A Theoretical Interpretation for RAML—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified