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 61–70 of 639 papers

TitleStatusHype
A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection—0
Agreement on Target-bidirectional Neural Machine Translation—0
Active Learning for Structured Probabilistic Models With Histogram Approximation—0
A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction—0
A Practical Perspective on Latent Structured Prediction for Coreference Resolution—0
A General Theory for Structured Prediction with Smooth Convex Surrogates—0
Bayesian Kernel Methods for Natural Language Processing—0
Approximate Inference in Structured Instances with Noisy Categorical Observations—0
Approximate Dynamic Oracle for Dependency Parsing with Reinforcement Learning—0
A General-Purpose Algorithm for Constrained Sequential Inference—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified