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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 421–430 of 639 papers

TitleStatusHype
Gray-box inference for structured Gaussian process models—0
Reward Augmented Maximum Likelihood for Neural Structured Prediction—0
Learning to generalize to new compositions in image understanding—0
Estimation from Indirect Supervision with Linear MomentsCode0
Canonical Correlation Inference for Mapping Abstract Scenes to Text—0
Text Simplification as Tree Labeling—0
Structured prediction models for RNN based sequence labeling in clinical textCode0
Learning to Jointly Predict Ellipsis and Comparison Structures—0
Recognizing Salient Entities in Shopping Queries—0
Learning Structured Predictors from Bandit Feedback for Interactive NLP—0
Show:102550
← PrevPage 43 of 64Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified