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 121–130 of 639 papers

TitleStatusHype
A Neural Probabilistic Structured-Prediction Model for Transition-Based Dependency Parsing—0
Computing a partition function of a generalized pattern-based energy over a semiring—0
A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection—0
Accelerating Stochastic Gradient Descent using Predictive Variance Reduction—0
Bayesian Kernel Methods for Natural Language Processing—0
Consistent Multitask Learning with Nonlinear Output Relations—0
DeepSPIN: Deep Structured Prediction for Natural Language Processing—0
A Constrained Latent Variable Model for Coreference Resolution—0
Bandit Structured Prediction for Learning from Partial Feedback in Statistical Machine Translation—0
A Boosted Semi-Markov Perceptron—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified