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 481–490 of 639 papers

TitleStatusHype
A New Smooth Approximation to the Zero One Loss with a Probabilistic Interpretation—0
Super-Resolution with Deep Convolutional Sufficient StatisticsCode0
Efficient non-greedy optimization of decision trees—0
Train and Test Tightness of LP Relaxations in Structured Prediction—0
Comparative Analysis between Notations to Classify Named Entities using Conditional Random Fields—0
On Correcting Inputs: Inverse Optimization for Online Structured Prediction—0
IllinoisSL: A JAVA Library for Structured Prediction—0
Structured Prediction with Output Embeddings for Semantic Image Annotation—0
An Improved Non-monotonic Transition System for Dependency Parsing—0
Extracting Relations between Non-Standard Entities using Distant Supervision and Imitation Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified