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 401–410 of 639 papers

TitleStatusHype
The Sum-Product Theorem: A Foundation for Learning Tractable Models—0
A Fully Convolutional Neural Network based Structured Prediction Approach Towards the Retinal Vessel Segmentation—0
Log-time and Log-space Extreme ClassificationCode0
The Concrete Distribution: A Continuous Relaxation of Discrete Random VariablesCode0
A Study of Imitation Learning Methods for Semantic Role Labeling—0
Introducing DRAIL -- a Step Towards Declarative Deep Relational Learning—0
Inside-Outside and Forward-Backward Algorithms Are Just Backprop (tutorial paper)—0
Posterior regularization for Joint Modeling of Multiple Structured Prediction Tasks with Soft Constraints—0
Proceedings of the Workshop on Structured Prediction for NLP—0
Regularizing Text Categorization with Clusters of Words—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified