Papers One-Shot Learning
“One-Shot Learning” 태그가 달린 논문 318편 · 필터 해제
One Shot Learning for Edge Detection on Point Clouds
Each scanner possesses its unique characteristics and exhibits its distinct sampling error distribution. Training a network on a dataset that includes data collected from different scanners is less effective than trainin…
One-Shot LearningEdge DetectionPoint CloudsOne-shot learning for the complex dynamical behaviors of weakly nonlinear forced oscillators
Extrapolative prediction of complex nonlinear dynamics remains a central challenge in engineering. This study proposes a one-shot learning method to identify global frequency-response curves from a single excitation time…
One-Shot LearningTraining Data Size Sensitivity in Unsupervised Rhyme Recognition
Rhyme is deceptively intuitive: what is or is not a rhyme is constructed historically, scholars struggle with rhyme classification, and people disagree on whether two words are rhymed or not. This complicates automated r…
One-Shot LearningFederatedFactory: Generative One-Shot Learning for Extremely Non-IID Distributed Scenarios
Federated Learning (FL) enables distributed optimization without compromising data sovereignty. Yet, where local label distributions are mutually exclusive, standard weight aggregation fails due to conflicting optimizati…
Distributed OptimizationFederated LearningOne-Shot LearningRegime-aware financial volatility forecasting via in-context learning
This work introduces a regime-aware in-context learning framework that leverages large language models (LLMs) for financial volatility forecasting under nonstationary market conditions. The proposed approach deploys pret…
One-Shot LearningFrom Native Memes to Global Moderation: Cross-Cultural Evaluation of Vision-Language Models for Hateful Meme Detection
Cultural context profoundly shapes how people interpret online content, yet vision-language models (VLMs) remain predominantly trained through Western or English-centric lenses. This limits their fairness and cross-cultu…
One-Shot LearningOne-Shot Identification with Different Neural Network Approaches
Convolutional neural networks (CNNs) have been widely used in the computer vision community, significantly improving the state-of-the-art. But learning good features often is computationally expensive in machine learning…
One-Shot LearningFace RecognitionCoordinate Matrix Machine: A Human-level Concept Learning to Classify Very Similar Documents
Human-level concept learning argues that humans typically learn new concepts from a single example, whereas machine learning algorithms typically require hundreds of samples to learn a single concept. Our brain subconsci…
One-Shot LearningTraining and Evaluation of Guideline-Based Medical Reasoning in LLMs
Machine learning for early prediction in medicine has recently shown breakthrough performance, however, the focus on improving prediction accuracy has led to a neglect of faithful explanations that are required to gain t…
Time Series ForecastingOne-Shot LearningSinSEMI: A One-Shot Image Generation Model and Data-Efficient Evaluation Framework for Semiconductor Inspection Equipment
In the early stages of semiconductor equipment development, obtaining large quantities of raw optical images poses a significant challenge. This data scarcity hinder the advancement of AI-powered solutions in semiconduct…
One-Shot LearningImage GenerationOn the Dataless Training of Neural Networks
This paper surveys studies on the use of neural networks for optimization in the training-data-free setting. Specifically, we examine the dataless application of neural network architectures in optimization by re-paramet…
Image ReconstructionZero-Shot LearningOne-Shot LearningO$^3$Afford: One-Shot 3D Object-to-Object Affordance Grounding for Generalizable Robotic Manipulation
Grounding object affordance is fundamental to robotic manipulation as it establishes the critical link between perception and action among interacting objects. However, prior works predominantly focus on predicting singl…
Few-Shot LearningOne-Shot LearningA Scalable and High Availability Solution for Recommending Resolutions to Problem Tickets
Resolution of incidents or problem tickets is a common theme in service industries in any sector, including billing and charging systems in telecom domain. Machine learning can help to identify patterns and suggest resol…
One-Shot LearningAdaptive Noise Resilient Keyword Spotting Using One-Shot Learning
Keyword spotting (KWS) is a key component of smart devices, enabling efficient and intuitive audio interaction. However, standard KWS systems deployed on embedded devices often suffer performance degradation under real-w…
Keyword SpottingOne-Shot LearningInteractive Instance Annotation with Siamese Networks
Annotating instance masks is time-consuming and labor-intensive. A promising solution is to predict contours using a deep learning model and then allow users to refine them. However, most existing methods focus on in-dom…
Object TrackingOne-Shot LearningFederated One-Shot Learning with Data Privacy and Objective-Hiding
Privacy in federated learning is crucial, encompassing two key aspects: safeguarding the privacy of clients' data and maintaining the privacy of the federator's objective from the clients. While the first aspect has been…
Federated LearningInformation RetrievalKnowledge DistillationOne-Shot Learning+1Transductive One-Shot Learning Meet Subspace Decomposition
One-shot learning focuses on adapting pretrained models to recognize newly introduced and unseen classes based on a single labeled image. While variations of few-shot and zero-shot learning exist, one-shot learning remai…
One-Shot LearningZero-Shot LearningPVChat: Personalized Video Chat with One-Shot Learning
Video large language models (ViLLMs) excel in general video understanding, e.g., recognizing activities like talking and eating, but struggle with identity-aware comprehension, such as "Wilson is receiving chemotherapy" …
One-Shot LearningQuestion AnsweringVideo UnderstandingRepresenting Signs as Signs: One-Shot ISLR to Facilitate Functional Sign Language Technologies
Isolated Sign Language Recognition (ISLR) is crucial for scalable sign language technology, yet language-specific approaches limit current models. To address this, we propose a one-shot learning approach that generalises…
One-Shot LearningSign Language RecognitionOne-Shot Learning for k-SAT
Consider a $k$-SAT formula $\Phi$ where every variable appears at most $d$ times, and let $\sigma$ be a satisfying assignment of $\Phi$ sampled proportionally to $e^{\beta m(\sigma)}$ where $m(\sigma)$ is the number of v…
One-Shot Learning