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 511520 of 639 papers

TitleStatusHype
Learning Where to Sample in Structured PredictionCode0
The Logic of AMR: Practical, Unified, Graph-Based Sentence Semantics for NLP0
Hands-on Learning to Search for Structured Prediction0
Transforming Dependencies into Phrase StructuresCode0
Robobarista: Object Part based Transfer of Manipulation Trajectories from Crowd-sourcing in 3D Pointclouds0
Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction0
Structured Prediction of Sequences and Trees using Infinite Contexts0
Bethe Projections for Non-Local Inference0
Learning Fast-Mixing Models for Structured PredictionCode0
Optimizing Text Quantifiers for Multivariate Loss Functions0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified