نتایج جستجو برای: for instance

تعداد نتایج: 10357184  

Journal: :IEEE Transactions on Pattern Analysis and Machine Intelligence 2010

Journal: :International Journal of Advanced Trends in Computer Science and Engineering 2020

Journal: :ACM Transactions on Asian and Low-Resource Language Information Processing 2023

Prompt learning has emerged as a new paradigm for leveraging pre-trained language models (PLMs) and shown promising results in downstream tasks with only slight increase parameters. However, the current usage of fixed prompts, whether discrete or continuous, assumes that all samples within task share same prompt. This assumption may not hold diverse require different prompt information. To addr...

Journal: :Neurocomputing 2023

In this paper, we introduce TIVE, a Toolbox for Identifying Video instance segmentation Errors. By directly operating output prediction files, TIVE defines isolated error types and weights each type’s damage to mAP, the purpose of distinguishing model characters. decomposing localization quality in spatial–temporal dimensions, model’s potential drawbacks on spatial temporal association can be r...

2008
Yangqing Jia Changshui Zhang

Multiple instance learning (MIL) is a branch of machine learning that attempts to learn information from bags of instances. Many real-world applications such as localized content-based image retrieval and text categorization can be viewed as MIL problems. In this paper, we propose a new graph-based semi-supervised learning approach for multiple instance learning. By defining an instance-level g...

Journal: :Electronic Colloquium on Computational Complexity (ECCC) 2013
Gregory Valiant Paul Valiant

We consider the problem of verifying the identity of a distribution: Given the description of a distribution over a discrete support p = (p1, p2, . . . , pn), how many samples (independent draws) must one obtain from an unknown distribution, q, to distinguish, with high probability, the case that p = q from the case that the total variation distance (L1 distance) ||p− q||1 ≥ ε? We resolve this ...

2012
Guoqing Liu Jianxin Wu Zhi-Hua Zhou

The goal of traditional multi-instance learning (MIL) is to predict the labels of the bags, whereas in many real applications, it is desirable to get the instance labels, especially the labels of key instances that trigger the bag labels, in addition to getting bag labels. Such a problem has been largely unexplored before. In this paper, we formulate the Key Instance Detection (KID) problem, an...

2007
James Foulds

Multi-instance (MI) learning is a variant of supervised machine learning, where each learning example contains a bag of instances instead of just a single feature vector. MI learning has applications in areas such as drug activity prediction, fruit disease management and image classification. This thesis investigates the case where each instance has a weight value determining the level of influ...

Journal: :Applied Mathematics and Computer Science 2014
Liming Yuan Jiafeng Liu Xianglong Tang

Multiple-Instance Learning (MIL) has attracted much attention of the machine learning community in recent years and many real-world applications have been successfully formulated as MIL problems. Over the past few years, several Instance Selection-based MIL (ISMIL) algorithms have been presented by using the concept of the embedding space. Although they delivered very promising performance, the...

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