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 201–210 of 639 papers

TitleStatusHype
GeoF: Geodesic Forests for Learning Coupled Predictors—0
CaLcs: Continuously Approximating Longest Common Subsequence for Sequence Level Optimization—0
Exact Inference in High-order Structured Prediction—0
An Online Algorithm for Learning over Constrained Latent Representations using Multiple Views—0
Experiments with crowdsourced re-annotation of a POS tagging data set—0
Explaining Fast Improvement in Online Imitation Learning—0
Explaining Large Language Model-Based Neural Semantic Parsers (Student Abstract)—0
Candidate Constrained CRFs for Loss-Aware Structured Prediction—0
Extracting Relations between Non-Standard Entities using Distant Supervision and Imitation Learning—0
Deeply Learning the Messages in Message Passing Inference—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified