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 626–639 of 639 papers

TitleStatusHype
Imitation learning for language generation from unaligned data—0
Imitation learning for structured prediction in natural language processing—0
Importance Weighted Structure Learning for Scene Graph Generation—0
Improved CCG Parsing with Semi-supervised Supertagging—0
Improved Dynamic Memory Network for Dialogue Act Classification with Adversarial Training—0
Improving Joint Training of Inference Networks and Structured Prediction Energy Networks—0
Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction—0
Increasing the Generalisation Capacity of Conditional VAEs—0
Inferring Interpersonal Relations in Narrative Summaries—0
Inside-Outside and Forward-Backward Algorithms Are Just Backprop (tutorial paper)—0
Integer Linear Programming formulations in Natural Language Processing—0
Integrated Inference and Learning of Neural Factors in Structural Support Vector Machines—0
Integrating Tree Structures and Graph Structures with Neural Networks to Classify Discussion Discourse Acts—0
Introducing DRAIL -- a Step Towards Declarative Deep Relational Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified