SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

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Showing 5676–5700 of 14581 papers

TitleStatusHype
The STEM-ECR Dataset: Grounding Scientific Entity References in STEM Scholarly Content to Authoritative Encyclopedic and Lexicographic Sources—0
The Stochastic Replica Approach to Machine Learning: Stability and Parameter Optimization—0
The Strength of the Weakest Supervision: Topic Classification Using Class Labels—0
The structure of evolved representations across different substrates for artificial intelligence—0
The SUMMA Platform Prototype—0
The SVM Classifier Based on the Modified Particle Swarm Optimization—0
The TALP-UPC Approach to System Selection: Asiya Features and Pairwise Classification Using Random Forests—0
The taraX\"U corpus of human-annotated machine translations—0
The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification—0
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey—0
The THUMOS Challenge on Action Recognition for Videos "in the Wild"—0
The UMCD Dataset—0
The UniTN Discourse Parser in CoNLL 2015 Shared Task: Token-level Sequence Labeling with Argument-specific Models—0
The Univariate Flagging Algorithm (UFA): a Fully-Automated Approach for Identifying Optimal Thresholds in Data—0
The University of Helsinki Submission to the WMT19 Parallel Corpus Filtering Task—0
The UN Parallel Corpus Annotated for Translation Direction—0
The use of Convolutional Neural Networks for signal-background classification in Particle Physics experiments—0
The use of deep learning in image segmentation, classification and detection—0
The Use of Mutual Coherence to Prove ^1/^0-Equivalence in Classification Problems—0
The Use of Unlabeled Data versus Labeled Data for Stopping Active Learning for Text Classification—0
The Utility of Abstaining in Binary Classification—0
The Utility of General Domain Transfer Learning for Medical Language Tasks—0
The UWNLP system at SemEval-2018 Task 7: Neural Relation Extraction Model with Selectively Incorporated Concept Embeddings—0
The Variational Deficiency Bottleneck—0
The Variational Homoencoder: Learning to Infer High-Capacity Generative Models from Few Examples—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KNNAccuracy93.1—Unverified
2RFAccuracy92.96—Unverified
3CARTAccuracy92.82—Unverified
4LDAAccuracy77.22—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified
2XBNETAccuracy100—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy42—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy67.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy68.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy13.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy90.6—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified