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 561–570 of 639 papers

TitleStatusHype
Simultaneous Twin Kernel Learning using Polynomial Transformations for Structured Prediction—0
Perceptron-like Algorithms and Generalization Bounds for Learning to Rank—0
A New Framework for Sign Language Recognition based on 3D Handshape Identification and Linguistic Modeling—0
Undirected Machine Translation with Discriminative Reinforcement Learning—0
A Hybrid Loss for Multiclass and Structured Prediction—0
A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing—0
Senti-LSSVM: Sentiment-Oriented Multi-Relation Extraction with Latent Structural SVM—0
Improved CCG Parsing with Semi-supervised Supertagging—0
Locally Non-Linear Learning for Statistical Machine Translation via Discretization and Structured Regularization—0
SpeedMachines: Anytime Structured Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified