Papers General Classification
“General Classification” 태그가 달린 논문 14,585편 · 필터 해제
Continuous Indeterminate Probability Neural Network
This paper introduces a general model called CIPNN - Continuous Indeterminate Probability Neural Network, and this model is based on IPNN, which is used for discrete latent random variables. Currently, posterior of conti…
ClassificationDecoderGeneral ClassificationVideo traffic identification with novel feature extraction and selection method
In recent years, the rapid rise of video applications has led to an explosion of Internet video traffic, thereby posing severe challenges to network management. Therefore, effectively identifying and managing video traff…
feature selectionGeneral ClassificationActive Learning and Bayesian Optimization: a Unified Perspective to Learn with a Goal
Science and Engineering applications are typically associated with expensive optimization problems to identify optimal design solutions and states of the system of interest. Bayesian optimization and active learning comp…
Active LearningBayesian OptimizationGeneral ClassificationSparsity based morphological identification of heartbeats
The electrocardiogram (ECG) is one of the most common primary tests to evaluate the health of the heart. Reliable automatic interpretation of ECG records is crucial to the goal of improving public health. It can enable a…
General ClassificationFair and Optimal Classification via Post-Processing
To mitigate the bias exhibited by machine learning models, fairness criteria can be integrated into the training process to ensure fair treatment across all demographics, but it often comes at the expense of model perfor…
AttributeClassificationDecision MakingFairness+1Hierarchical classification at multiple operating points
Many classification problems consider classes that form a hierarchy. Classifiers that are aware of this hierarchy may be able to make confident predictions at a coarse level despite being uncertain at the fine-grained le…
General ClassificationAssociation Graph Learning for Multi-Task Classification with Category Shifts
In this paper, we focus on multi-task classification, where related classification tasks share the same label space and are learned simultaneously. In particular, we tackle a new setting, which is more realistic than cur…
General ClassificationGraph LearningLesion ClassificationSkin Lesion Classification+1Detecting Label Errors in Token Classification Data
Mislabeled examples are a common issue in real-world data, particularly for tasks like token classification where many labels must be chosen on a fine-grained basis. Here we consider the task of finding sentences that co…
General ClassificationToken ClassificationSVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models
Vision-language models such as CLIP are pretrained on large volumes of internet sourced image and text pairs, and have been shown to sometimes exhibit impressive zero- and low-shot image classification performance. Howev…
General Classificationimage-classificationImage ClassificationRepresentation LearningExplainable Abuse Detection as Intent Classification and Slot Filling
To proactively offer social media users a safe online experience, there is a need for systems that can detect harmful posts and promptly alert platform moderators. In order to guarantee the enforcement of a consistent po…
Abuse DetectionGeneral Classificationintent-classificationIntent Classification+1A kernel-based quantum random forest for improved classification
The emergence of Quantum Machine Learning (QML) to enhance traditional classical learning methods has seen various limitations to its realisation. There is therefore an imperative to develop quantum models with unique mo…
General ClassificationQuantum Machine LearningLearning Temporal Resolution in Spectrogram for Audio Classification
The audio spectrogram is a time-frequency representation that has been widely used for audio classification. One of the key attributes of the audio spectrogram is the temporal resolution, which depends on the hop size us…
Audio ClassificationGeneral ClassificationDomain Adaptation for Question Answering via Question Classification
Question answering (QA) has demonstrated impressive progress in answering questions from customized domains. Nevertheless, domain adaptation remains one of the most elusive challenges for QA systems, especially when QA s…
Domain AdaptationGeneral ClassificationQuestion AnsweringSupervised Dimensionality Reduction and Image Classification Utilizing Convolutional Autoencoders
The joint optimization of the reconstruction and classification error is a hard non convex problem, especially when a non linear mapping is utilized. In order to overcome this obstacle, a novel optimization strategy is p…
Deep LearningDimensionality ReductionGeneral Classificationimage-classification+2Semi-supervised classification using a supervised autoencoder for biomedical applications
In this paper we present a new approach to solve semi-supervised classification tasks for biomedical applications, involving a supervised autoencoder network. We create a network architecture that encodes labels into the…
General ClassificationStop&Hop: Early Classification of Irregular Time Series
Early classification algorithms help users react faster to their machine learning model's predictions. Early warning systems in hospitals, for example, let clinicians improve their patients' outcomes by accurately predic…
Early ClassificationGeneral ClassificationIrregular Time SeriesTime Series+1Autism spectrum disorder classification based on interpersonal neural synchrony: Can classification be improved by dyadic neural biomarkers using unsupervised graph representation learning?
Research in machine learning for autism spectrum disorder (ASD) classification bears the promise to improve clinical diagnoses. However, recent studies in clinical imaging have shown the limited generalization of biomark…
General ClassificationGraph Representation LearningRepresentation LearningAcceleration of Subspace Learning Machine via Particle Swarm Optimization and Parallel Processing
Built upon the decision tree (DT) classification and regression idea, the subspace learning machine (SLM) has been recently proposed to offer higher performance in general classification and regression tasks. Its perform…
ClassificationGeneral ClassificationregressionToward Interpretable Sleep Stage Classification Using Cross-Modal Transformers
Accurate sleep stage classification is significant for sleep health assessment. In recent years, several machine-learning based sleep staging algorithms have been developed , and in particular, deep-learning based algori…
Automatic Sleep Stage ClassificationDeep LearningGeneral ClassificationMultimodal Sleep Stage Detection+3Visual Localization via Few-Shot Scene Region Classification
Visual (re)localization addresses the problem of estimating the 6-DoF (Degree of Freedom) camera pose of a query image captured in a known scene, which is a key building block of many computer vision and robotics applica…
General ClassificationMemorizationMeta-LearningVisual Localization