main webpage W Topic Data Mining arXiv (Cornell University) Diverse Data Augmentation with Diffusions for Effective Test-time Prompt Tuning 2023 Benefiting from prompt tuning, recent years have witnessed the promising performance of pre-trained vision-language models, e.g., CLIP, on versatile downstream tasks. In this paper, we focus on a particular setting of learning adaptive prompts on the fly for … Article Open Data Mining Open Article Page

Data Mining

Process of extracting and discovering patterns in large data sets Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Critical Symbolic Virtual Narrative Open Data Mining Open Article Page

Exploring foci of: arXiv (Cornell University) Diverse Data Augmentation with Diffusions for Effective Test-time Prompt Tuning 2023 Benefiting from prompt tuning, recent years have witnessed the promising performance of pre-trained vision-language models, e.g., CLIP, on versatile downstream tasks. In this paper, we focus on a particular setting of learning adaptive prompts on the fly for each test sample from an unseen new domain, which is known as test-time prompt tuning (TPT). Existing TPT methods typically rely on data augmentation and confidence selection. However, conventional data augmentation techniques, e.g., random resized crops, suff… Open Article Page

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Explore Data Mining W Topic Data Mining arXiv (Cornell University) Diverse Data Augmentation with Diffusions for Effective Test-time Prompt Tuning 2023 Benefiting from prompt tuning, recent years have witnessed the promising performance of pre-trained vision-language models, e.g., CLIP, on versatile downstream tasks. In this paper, we focus on a particular setting of learning adaptive prompts on the fly for … Article Critical Symbolic Virtual Narrative Open Data Mining Open Article Page