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 191–200 of 639 papers

TitleStatusHype
Agreement on Target-bidirectional Neural Machine Translation—0
Computing a partition function of a generalized pattern-based energy over a semiring—0
Complex Structure Leads to Overfitting: A Structure Regularization Decoding Method for Natural Language Processing—0
Complex Relations in a Deep Structured Prediction Model for Fine Image Segmentation—0
Comparative Analysis between Notations to Classify Named Entities using Conditional Random Fields—0
A Rate Distortion Approach for Semi-Supervised Conditional Random Fields—0
Active Learning in Video Tracking—0
Compact Representation of Uncertainty in Clustering—0
A Projected Gradient Descent Method for CRF Inference allowing End-To-End Training of Arbitrary Pairwise Potentials—0
Combining Active Learning and Partial Annotation for Domain Adaptation of a Japanese Dependency Parser—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified