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 231–240 of 639 papers

TitleStatusHype
Gaussian Processes for Natural Language Processing—0
Generalization Analysis on Learning with a Concurrent Verifier—0
Combining Active Learning and Partial Annotation for Domain Adaptation of a Japanese Dependency Parser—0
Generic Oracles for Structured Prediction—0
GeoF: Geodesic Forests for Learning Coupled Predictors—0
Geometric Matrix Completion with Deep Conditional Random Fields—0
Global Model for Hierarchical Multi-Label Text Classification—0
Gradient-based Inference for Networks with Output Constraints—0
Graph-Based Lexicon Expansion with Sparsity-Inducing Penalties—0
Deep imitation learning for molecular inverse problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified