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 581–590 of 639 papers

TitleStatusHype
End-to-End Neural Relation Extraction with Global Optimization—0
Energy-based Neural Modelling for Large-Scale Multiple Domain Dialogue State Tracking—0
Energy Disaggregation via Discriminative Sparse Coding—0
Energy Disaggregation with Semi-supervised Sparse Coding—0
Ensemble Distillation for Structured Prediction: Calibrated, Accurate, Fast-Choose Three—0
Entropy-Based Latent Structured Output Prediction—0
Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces—0
Exact Inference in High-order Structured Prediction—0
Experiments with crowdsourced re-annotation of a POS tagging data set—0
Explaining Fast Improvement in Online Imitation Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified