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 201–210 of 639 papers

TitleStatusHype
A Graph-Based Framework for Structured Prediction Tasks in Sanskrit—0
Cocktail Party Processing via Structured Prediction—0
A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction—0
CMU at SemEval-2016 Task 8: Graph-based AMR Parsing with Infinite Ramp Loss—0
A Practical Perspective on Latent Structured Prediction for Coreference Resolution—0
A General Theory for Structured Prediction with Smooth Convex Surrogates—0
Active Learning for Structured Probabilistic Models With Histogram Approximation—0
Accelerating Stochastic Gradient Descent using Predictive Variance Reduction—0
Clouds of Oriented Gradients for 3D Detection of Objects, Surfaces, and Indoor Scene Layouts—0
Closed-Form Training of Mahalanobis Distance for Supervised Clustering—0
Show:102550
← PrevPage 21 of 64Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified