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

Showing 631639 of 639 papers

TitleStatusHype
An Introduction to Conditional Random Fields0
Twin gaussian processes for structured prediction0
A Rate Distortion Approach for Semi-Supervised Conditional Random Fields0
Search-based Structured Prediction0
Structured ranking learning using cumulative distribution networks0
Tighter Bounds for Structured Estimation0
Partially Observed Maximum Entropy Discrimination Markov Networks0
Robust Near-Isometric Matching via Structured Learning of Graphical Models0
Efficient multiple hyperparameter learning for log-linear models0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified