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 301–310 of 639 papers

TitleStatusHype
Doubly Reparameterized Importance Weighted Structure Learning for Scene Graph Generation—0
Bayesian Kernel Methods for Natural Language Processing—0
Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures—0
Document Context Neural Machine Translation with Memory Networks—0
Bandit Structured Prediction for Learning from Partial Feedback in Statistical Machine Translation—0
A Neural Probabilistic Structured-Prediction Model for Transition-Based Dependency Parsing—0
DiverseNet: When One Right Answer is not Enough—0
Distributionally Robust Graphical Models—0
Distributed Training of Structured SVM—0
An Empirical Exploration of Local Ordering Pre-training for Structured Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified