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 291–300 of 639 papers

TitleStatusHype
A New Framework for Sign Language Recognition based on 3D Handshape Identification and Linguistic Modeling—0
Efficient and Consistent Adversarial Bipartite Matching—0
Effective Token Graph Modeling using a Novel Labeling Strategy for Structured Sentiment Analysis—0
Effectiveness of Function Matching in Driving Scene Recognition—0
Effective Decoding in Graph Auto-Encoder using Triadic Closure—0
Belief Propagation in Conditional RBMs for Structured Prediction—0
A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing—0
A Fenchel-Young Loss Approach to Data-Driven Inverse Optimization—0
Dynamic Feature Selection for Dependency Parsing—0
Dual Coordinate Descent Algorithms for Efficient Large Margin Structured Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified