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 541–550 of 639 papers

TitleStatusHype
Constrained Structure Learning for Scene Graph Generation—0
Constructing Information Networks Using One Single Model—0
Counterfactual Learning from Bandit Feedback under Deterministic Logging : A Case Study in Statistical Machine Translation—0
Cross-Lingual Discriminative Learning of Sequence Models with Posterior Regularization—0
Data-efficient Active Learning for Structured Prediction with Partial Annotation and Self-Training—0
Deep imitation learning for molecular inverse problems—0
Deep Learning in Lexical Analysis and Parsing—0
Deeply Learning the Messages in Message Passing Inference—0
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation—0
DeepSPIN: Deep Structured Prediction for Natural Language Processing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified