Papers General Classification
“General Classification” 태그가 달린 논문 14,585편 · 필터 해제
On the Limitations of Continual Learning for Malware Classification
Malicious software (malware) classification offers a unique challenge for continual learning (CL) regimes due to the volume of new samples received on a daily basis and the evolution of malware to exploit new vulnerabili…
Continual LearningGeneral ClassificationIncremental LearningMalware ClassificationUSB: A Unified Semi-supervised Learning Benchmark for Classification
Semi-supervised learning (SSL) improves model generalization by leveraging massive unlabeled data to augment limited labeled samples. However, currently, popular SSL evaluation protocols are often constrained to computer…
General ClassificationGPUSemi-Supervised Image ClassificationScalable Quantum Neural Networks for Classification
Many recent machine learning tasks resort to quantum computing to improve classification accuracy and training efficiency by taking advantage of quantum mechanics, known as quantum machine learning (QML). The variational…
Binary ClassificationGeneral ClassificationQuantum Machine LearningPyABSA: A Modularized Framework for Reproducible Aspect-based Sentiment Analysis
The advancement of aspect-based sentiment analysis (ABSA) has urged the lack of a user-friendly framework that can largely lower the difficulty of reproducing state-of-the-art ABSA performance, especially for beginners. …
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Data AugmentationGeneral Classification+4Inductive and Transductive Few-Shot Video Classification via Appearance and Temporal Alignments
We present a novel method for few-shot video classification, which performs appearance and temporal alignments. In particular, given a pair of query and support videos, we conduct appearance alignment via frame-level fea…
General ClassificationVideo ClassificationLarge Scale Radio Frequency Signal Classification
Existing datasets used to train deep learning models for narrowband radio frequency (RF) signal classification lack enough diversity in signal types and channel impairments to sufficiently assess model performance in the…
DiversityGeneral ClassificationVisual Knowledge Tracing
Each year, thousands of people learn new visual categorization tasks -- radiologists learn to recognize tumors, birdwatchers learn to distinguish similar species, and crowd workers learn how to annotate valuable data for…
Autonomous DrivingGeneral ClassificationKnowledge TracingContributions of Shape, Texture, and Color in Visual Recognition
We investigate the contributions of three important features of the human visual system (HVS)~ -- ~shape, texture, and color ~ -- ~to object classification. We build a humanoid vision engine (HVE) that explicitly and sep…
AttributeGeneral ClassificationObject RecognitionZero-Shot LearningSemi-Supervised Temporal Action Detection with Proposal-Free Masking
Existing temporal action detection (TAD) methods rely on a large number of training data with segment-level annotations. Collecting and annotating such a training set is thus highly expensive and unscalable. Semi-supervi…
Action DetectionGeneral ClassificationSemi-Supervised Action DetectionA Data-Efficient Deep Learning Framework for Segmentation and Classification of Histopathology Images
The current study of cell architecture of inflammation in histopathology images commonly performed for diagnosis and research purposes excludes a lot of information available on the biopsy slide. In autoimmune diseases, …
General ClassificationMedical Image SegmentationSegmentationTabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
We present TabPFN, a trained Transformer that can do supervised classification for small tabular datasets in less than a second, needs no hyperparameter tuning and is competitive with state-of-the-art classification meth…
AutoMLBayesian InferenceGeneral ClassificationGPU+4RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network
This work introduces RevSilo, the first reversible bidirectional multi-scale feature fusion module. Like other reversible methods, RevSilo eliminates the need to store hidden activations by recomputing them. However, exi…
General Classificationimage-classificationImage ClassificationInstance Segmentation+1Protoformer: Embedding Prototypes for Transformers
Transformers have been widely applied in text classification. Unfortunately, real-world data contain anomalies and noisy labels that cause challenges for state-of-art Transformers. This paper proposes Protoformer, a nove…
ClassificationGeneral ClassificationLanguage ModellingLarge Language Model+4Truly Unordered Probabilistic Rule Sets for Multi-class Classification
Rule set learning has long been studied and has recently been frequently revisited due to the need for interpretable models. Still, existing methods have several shortcomings: 1) most recent methods require a binary feat…
General ClassificationMulti-class ClassificationDifferentiable Top-k Classification Learning
The top-k classification accuracy is one of the core metrics in machine learning. Here, k is conventionally a positive integer, such as 1 or 5, leading to top-1 or top-5 training objectives. In this work, we relax this a…
General ClassificationImage ClassificationEvaluating histopathology transfer learning with ChampKit
Histopathology remains the gold standard for diagnosis of various cancers. Recent advances in computer vision, specifically deep learning, have facilitated the analysis of histopathology images for various tasks, includi…
BenchmarkingCell DetectionGeneral Classificationimage-classification+3LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks
Fine-tuning pretrained language models (LMs) without making any architectural changes has become a norm for learning various language downstream tasks. However, for non-language downstream tasks, a common practice is to …
BIG-bench Machine LearningGeneral ClassificationInductive BiasregressionLocalizing Semantic Patches for Accelerating Image Classification
Existing works often focus on reducing the architecture redundancy for accelerating image classification but ignore the spatial redundancy of the input image. This paper proposes an efficient image classification pipelin…
ClassificationGeneral Classificationimage-classificationImage ClassificationHopular: Modern Hopfield Networks for Tabular Data
While Deep Learning excels in structured data as encountered in vision and natural language processing, it failed to meet its expectations on tabular data. For tabular data, Support Vector Machines (SVMs), Random Forests…
Deep LearningGeneral ClassificationFailure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed
Failure detection in automated image classification is a critical safeguard for clinical deployment. Detected failure cases can be referred to human assessment, ensuring patient safety in computer-aided clinical decision…
BenchmarkingBinary ClassificationDecision MakingGeneral Classification+4