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 426–450 of 639 papers

TitleStatusHype
Learning to Jointly Predict Ellipsis and Comparison Structures—0
Sequence-based Structured Prediction for Semantic Parsing—0
Text Simplification as Tree Labeling—0
Recognizing Salient Entities in Shopping Queries—0
Learning Structured Predictors from Bandit Feedback for Interactive NLP—0
Structured prediction models for RNN based sequence labeling in clinical textCode0
A Probabilistic Generative Grammar for Semantic ParsingCode0
Slack and Margin Rescaling as Convex Extensions of Supermodular FunctionsCode0
Semi-supervised structured output prediction by local linear regression and sub-gradient descent—0
Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction—0
Stochastic Structured Prediction under Bandit FeedbackCode0
Feature Space Optimization for Semantic Video SegmentationCode0
Closed-Form Training of Mahalanobis Distance for Supervised Clustering—0
Situation Recognition: Visual Semantic Role Labeling for Image UnderstandingCode0
Structured Prediction of Unobserved Voxels From a Single Depth Image—0
Three-Dimensional Object Detection and Layout Prediction Using Clouds of Oriented Gradients—0
Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction—0
CLIP@UMD at SemEval-2016 Task 8: Parser for Abstract Meaning Representation using Learning to Search—0
CMU at SemEval-2016 Task 8: Graph-based AMR Parsing with Infinite Ramp Loss—0
Joint Event Extraction via Recurrent Neural NetworksCode0
Weighting Finite-State Transductions With Neural Context—0
Using Context to Predict the Purpose of Argumentative Writing Revisions—0
LSTM CCG Parsing—0
Transition-Based Syntactic Linearization with Lookahead FeaturesCode0
Agreement on Target-bidirectional Neural Machine Translation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified