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 411–420 of 639 papers

TitleStatusHype
Temporal Action Localization by Structured Maximal Sums—0
Tensor Composition Net for Visual Relationship Prediction—0
Text2Math: End-to-end Parsing Text into Math Expressions—0
Text-based Speaker Identification on Multiparty Dialogues Using Multi-document Convolutional Neural Networks—0
Text Simplification as Tree Labeling—0
The Effect of Higher-Order Dependency Features in Discriminative Phrase-Structure Parsing—0
The Logic of AMR: Practical, Unified, Graph-Based Sentence Semantics for NLP—0
The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding—0
The Structured Weighted Violations Perceptron Algorithm—0
The Sum-Product Theorem: A Foundation for Learning Tractable Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified