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 601–610 of 639 papers

TitleStatusHype
O Reconhecimento de Entidades Nomeadas por meio de Conditional Random Fields para a L\' Portuguesa (Named Entity Recognition with Conditional Random Fields for the Portuguese Language) [in Portuguese]—0
Parsing Models for Identifying Multiword Expressions—0
Dual Coordinate Descent Algorithms for Efficient Large Margin Structured Prediction—0
A Joint Phrasal and Dependency Model for Paraphrase Alignment—0
Cocktail Party Processing via Structured Prediction—0
Blending Learning and Inference in Structured Prediction—0
On Amortizing Inference Cost for Structured Prediction—0
Forest Reranking through Subtree Ranking—0
Parse, Price and Cut---Delayed Column and Row Generation for Graph Based Parsers—0
Utilizing Dependency Language Models for Graph-based Dependency Parsing Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified