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 511–520 of 639 papers

TitleStatusHype
Bayesian Kernel Methods for Natural Language Processing—0
Belief Propagation in Conditional RBMs for Structured Prediction—0
Bethe Projections for Non-Local Inference—0
Better Transition-Based AMR Parsing with a Refined Search Space—0
Beyond MLE: Investigating SEARNN for Low-Resourced Neural Machine Translation—0
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling—0
Blending Learning and Inference in Structured Prediction—0
Book Review: Linguistic Structure Prediction by Noah A. Smith—0
Boosting Information Extraction Systems with Character-level Neural Networks and Free Noisy Supervision—0
Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified