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 401–425 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
Unsupervised Neural Dependency ParsingCode0
Research on attention memory networks as a model for learning natural language inference—0
A Joint Model of Rhetorical Discourse Structure and Summarization—0
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak SupervisionCode0
Automatic measurement of vowel duration via structured predictionCode0
Frank-Wolfe Algorithms for Saddle Point ProblemsCode0
Sequence Segmentation Using Joint RNN and Structured Prediction Models—0
Learning Optimal Parameters for Multi-target Tracking with Contextual Interactions—0
Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities—0
Input Convex Neural NetworksCode0
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified