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 591600 of 639 papers

TitleStatusHype
Margin-based Decomposed Amortized Inference0
Online Relative Margin Maximization for Statistical Machine Translation0
The Effect of Higher-Order Dependency Features in Discriminative Phrase-Structure Parsing0
Fast and Robust Compressive Summarization with Dual Decomposition and Multi-Task Learning0
Joint Event Extraction via Structured Prediction with Global Features0
Bayesian Structured Prediction Using Gaussian ProcessesCode0
Manhattan Junction Catalogue for Spatial Reasoning of Indoor Scenes0
GeoF: Geodesic Forests for Learning Coupled Predictors0
Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets0
Part-Based Visual Tracking with Online Latent Structural Learning0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified