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 276–300 of 639 papers

TitleStatusHype
Book Review: Linguistic Structure Prediction by Noah A. Smith—0
Emotion-Conditioned Text Generation through Automatic Prompt Optimization—0
Blending Learning and Inference in Structured Prediction—0
A New Smooth Approximation to the Zero One Loss with a Probabilistic Interpretation—0
Efficient Structured Surrogate Loss and Regularization in Structured Prediction—0
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling—0
Efficient non-greedy optimization of decision trees—0
Beyond MLE: Investigating SEARNN for Low-Resourced Neural Machine Translation—0
A New Recurrent Neural CRF for Learning Non-linear Edge Features—0
Efficient Multi-Template Learning for Structured Prediction—0
Efficient multiple hyperparameter learning for log-linear models—0
Better Transition-Based AMR Parsing with a Refined Search Space—0
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses—0
Document-level Event Extraction with Efficient End-to-end Learning of Cross-event Dependencies—0
Bethe Projections for Non-Local Inference—0
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