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
An Embedding Framework for Consistent Polyhedral Surrogates—0
An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates—0
An Empirical Exploration of Local Ordering Pre-training for Structured Prediction—0
A Neural Probabilistic Structured-Prediction Model for Transition-Based Dependency Parsing—0
A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing—0
A New Framework for Sign Language Recognition based on 3D Handshape Identification and Linguistic Modeling—0
A New Recurrent Neural CRF for Learning Non-linear Edge Features—0
A New Smooth Approximation to the Zero One Loss with a Probabilistic Interpretation—0
An Improved Non-monotonic Transition System for Dependency Parsing—0
An Introduction to Conditional Random Fields—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified