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
Approximate Inference in Structured Instances with Noisy Categorical Observations—0
CLIP@UMD at SemEval-2016 Task 8: Parser for Abstract Meaning Representation using Learning to Search—0
Fast View Synthesis with Deep Stereo Vision—0
Classical Structured Prediction Losses for Sequence to Sequence Learning—0
Approximate Dynamic Oracle for Dependency Parsing with Reinforcement Learning—0
A General-Purpose Algorithm for Constrained Sequential Inference—0
Fast and Robust Compressive Summarization with Dual Decomposition and Multi-Task Learning—0
Feature Noising for Log-Linear Structured Prediction—0
Fast and Exact: ADMM-Based Discriminative Shape Segmentation with Loopy Part Models—0
Capturing Dialogue State Variable Dependencies with an Energy-based Neural Dialogue State Tracker—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified