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 261–270 of 639 papers

TitleStatusHype
Data-efficient Active Learning for Structured Prediction with Partial Annotation and Self-Training—0
Exact inference in structured prediction—0
Cross-Lingual Discriminative Learning of Sequence Models with Posterior Regularization—0
A Joint Phrasal and Dependency Model for Paraphrase Alignment—0
Iterative Instance Segmentation—0
Counterfactual Learning from Bandit Feedback under Deterministic Logging : A Case Study in Statistical Machine Translation—0
Integer Linear Programming formulations in Natural Language Processing—0
Inferring Interpersonal Relations in Narrative Summaries—0
Increasing the Generalisation Capacity of Conditional VAEs—0
A Joint Model of Rhetorical Discourse Structure and Summarization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified