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 171–180 of 639 papers

TitleStatusHype
NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-End Learning and Control—0
Structured and Localized Image Restoration—0
Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable ModelsCode0
Syntactic Structure Distillation Pretraining For Bidirectional Encoders—0
Active Imitation Learning with Noisy GuidanceCode1
Learning Constraints for Structured Prediction Using Rectifier NetworksCode0
Large scale evaluation of importance maps in automatic speech recognition—0
Learning Composable Energy Surrogates for PDE Order Reduction—0
The Structured Weighted Violations MIRACode0
StructPool: Structured Graph Pooling via Conditional Random FieldsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified