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 331–340 of 639 papers

TitleStatusHype
Regularizing Text Categorization with Clusters of Words—0
Reinforcement and Imitation Learning via Interactive No-Regret Learning—0
Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization—0
Research on attention memory networks as a model for learning natural language inference—0
Resource Constrained Structured Prediction—0
Retinal Vessel Segmentation under Extreme Low Annotation: A Generative Adversarial Network Approach—0
Reward Augmented Maximum Likelihood for Neural Structured Prediction—0
Risk Minimization in Structured Prediction using Orbit Loss—0
Robobarista: Learning to Manipulate Novel Objects via Deep Multimodal Embedding—0
Robobarista: Object Part based Transfer of Manipulation Trajectories from Crowd-sourcing in 3D Pointclouds—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified