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 131–140 of 639 papers

TitleStatusHype
Towards Sharper Generalization Bounds for Structured Prediction—0
Safe Screening for Sparse Conditional Random Fields—0
Multi-fidelity Stability for Graph Representation Learning—0
Effective Token Graph Modeling using a Novel Labeling Strategy for Structured Sentiment Analysis—0
SegMix: A Simple Structure-Aware Data Augmentation Method—0
Word Reordering for Zero-shot Cross-lingual Structured Prediction—0
Language Modelling via Learning to Rank—0
Unsupervised Cross-Lingual Transfer of Structured Predictors without Source DataCode0
Structured Energy Network as a dynamic loss function. Case study. A case study with multi-label Classification—0
Multi-task Learning with Domain Knowledge for Molecular Property Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified