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 111–120 of 639 papers

TitleStatusHype
CMU at SemEval-2016 Task 8: Graph-based AMR Parsing with Infinite Ramp Loss—0
A Practical Perspective on Latent Structured Prediction for Coreference Resolution—0
Cocktail Party Processing via Structured Prediction—0
A Neural Probabilistic Structured-Prediction Model for Transition-Based Dependency Parsing—0
A Graph-Based Framework for Structured Prediction Tasks in Sanskrit—0
Combining Active Learning and Partial Annotation for Domain Adaptation of a Japanese Dependency Parser—0
A Projected Gradient Descent Method for CRF Inference allowing End-To-End Training of Arbitrary Pairwise Potentials—0
Compact Representation of Uncertainty in Clustering—0
Comparative Analysis between Notations to Classify Named Entities using Conditional Random Fields—0
Bayesian Kernel Methods for Natural Language Processing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified