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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 276–300 of 639 papers

TitleStatusHype
Learning Distributions over Permutations and Rankings with Factorized Representations—0
Introducing DRAIL -- a Step Towards Declarative Deep Relational Learning—0
Iterative Instance Segmentation—0
Active learning with version spaces for object detection—0
A Structured Prediction Approach for Missing Value Imputation—0
Joint Event Extraction via Structured Prediction with Global Features—0
Deep imitation learning for molecular inverse problems—0
Keep it Surprisingly Simple: A Simple First Order Graph Based Parsing Model for Joint Morphosyntactic Parsing in Sanskrit—0
Knowledge Tracing in Sequential Learning of Inflected Vocabulary—0
Deeply Learning the Messages in Message Passing Inference—0
Language Classification and Segmentation of Noisy Documents in Hebrew Scripts—0
Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction—0
Large-Margin Learning of Submodular Summarization Models—0
Large Margin Semi-supervised Structured Output Learning—0
Large scale evaluation of importance maps in automatic speech recognition—0
Latent Structured Active Learning—0
Latent Structures for Coreference Resolution—0
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation—0
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations—0
Learning Adaptive Value of Information for Structured Prediction—0
Improving Joint Training of Inference Networks and Structured Prediction Energy Networks—0
A Survey of Active Learning for Natural Language Processing—0
Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing—0
A Structured Approach to Predicting Image Enhancement Parameters—0
Learning Discriminators as Energy Networks in Adversarial Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified