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 411420 of 639 papers

TitleStatusHype
Unsupervised Neural Dependency ParsingCode0
Research on attention memory networks as a model for learning natural language inference0
A Joint Model of Rhetorical Discourse Structure and Summarization0
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak SupervisionCode0
Automatic measurement of vowel duration via structured predictionCode0
Frank-Wolfe Algorithms for Saddle Point ProblemsCode0
Sequence Segmentation Using Joint RNN and Structured Prediction Models0
Learning Optimal Parameters for Multi-target Tracking with Contextual Interactions0
Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities0
Input Convex Neural NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified