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 211–220 of 639 papers

TitleStatusHype
Deep Learning in Lexical Analysis and Parsing—0
Fast and Exact: ADMM-Based Discriminative Shape Segmentation with Loopy Part Models—0
Fast and Robust Compressive Summarization with Dual Decomposition and Multi-Task Learning—0
A Study of Imitation Learning Methods for Semantic Role Labeling—0
Classical Structured Prediction Losses for Sequence to Sequence Learning—0
Fast View Synthesis with Deep Stereo Vision—0
CLIP@UMD at SemEval-2016 Task 8: Parser for Abstract Meaning Representation using Learning to Search—0
Feature Noising for Log-Linear Structured Prediction—0
Closed-Form Training of Mahalanobis Distance for Supervised Clustering—0
Deep imitation learning for molecular inverse problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified