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 451–460 of 639 papers

TitleStatusHype
Agreement on Target-bidirectional Neural Machine Translation—0
End-to-End Instance Segmentation with Recurrent AttentionCode0
Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs—0
Video Summarization with Long Short-term MemoryCode0
Local Perturb-and-MAP for Structured Prediction—0
A Consistent Regularization Approach for Structured Prediction—0
Structured Prediction Theory Based on Factor Graph Complexity—0
Linear-memory and Decomposition-invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes—0
Structured Prediction of 3D Human Pose with Deep Neural Networks—0
Semi-supervised learning of local structured output predictors—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified