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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 281–290 of 639 papers

TitleStatusHype
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling—0
Efficient non-greedy optimization of decision trees—0
Beyond MLE: Investigating SEARNN for Low-Resourced Neural Machine Translation—0
A New Recurrent Neural CRF for Learning Non-linear Edge Features—0
Efficient Multi-Template Learning for Structured Prediction—0
Efficient multiple hyperparameter learning for log-linear models—0
Better Transition-Based AMR Parsing with a Refined Search Space—0
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses—0
Document-level Event Extraction with Efficient End-to-end Learning of Cross-event Dependencies—0
Bethe Projections for Non-Local Inference—0
Show:102550
← PrevPage 29 of 64Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified