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 291–300 of 639 papers

TitleStatusHype
Integrating Tree Structures and Graph Structures with Neural Networks to Classify Discussion Discourse Acts—0
Memory Augmented Policy Optimization for Program Synthesis and Semantic ParsingCode0
A Structured Prediction Approach for Label RankingCode0
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation—0
Efficient and Consistent Adversarial Bipartite Matching—0
Pre- and In-Parsing Models for Neural Empty Category Detection—0
Manifold Structured Prediction—0
Sparse Stochastic Zeroth-Order Optimization with an Application to Bandit Structured Prediction—0
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations—0
Localized Structured Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified