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 4150 of 639 papers

TitleStatusHype
Active Imitation Learning with Noisy GuidanceCode1
StructPool: Structured Graph Pooling via Conditional Random FieldsCode1
Instance-Based Learning of Span Representations: A Case Study through Named Entity RecognitionCode1
Structured Prediction with Partial Labelling through the Infimum LossCode1
Learning with Differentiable Perturbed OptimizersCode1
Estimating Gradients for Discrete Random Variables by Sampling without ReplacementCode1
LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured PredictionCode1
Structured Output Learning with Conditional Generative FlowsCode1
Learning Approximate Inference Networks for Structured PredictionCode1
Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level ConstraintsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified