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 581–590 of 639 papers

TitleStatusHype
Cross-Lingual Discriminative Learning of Sequence Models with Posterior Regularization—0
Online Learning for Inexact Hypergraph Search—0
Dynamic Feature Selection for Dependency Parsing—0
Overcoming the Lack of Parallel Data in Sentence Compression—0
A Constrained Latent Variable Model for Coreference Resolution—0
Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction—0
Learning Max-Margin Tree Predictors—0
A Boosted Semi-Markov Perceptron—0
Sentence Compression with Joint Structural Inference—0
Graph-Based Posterior Regularization for Semi-Supervised Structured Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified