Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Grant, Christan"'
In recent research, contrastive learning has proven to be a highly effective method for representation learning and is widely used for dense retrieval. However, we identify that relying solely on contrastive learning can lead to suboptimal retrieval
Externí odkaz:
http://arxiv.org/abs/2403.14074
Autor:
Zhao, Chen, Jiang, Kai, Wu, Xintao, Wang, Haoliang, Khan, Latifur, Grant, Christan, Chen, Feng
The endeavor to preserve the generalization of a fair and invariant classifier across domains, especially in the presence of distribution shifts, becomes a significant and intricate challenge in machine learning. In response to this challenge, numero
Externí odkaz:
http://arxiv.org/abs/2311.13816
In the problem of online learning for changing environments, data are sequentially received one after another over time, and their distribution assumptions may vary frequently. Although existing methods demonstrate the effectiveness of their learning
Externí odkaz:
http://arxiv.org/abs/2306.01007
In an ideal world, deployed machine learning models will enhance our society. We hope that those models will provide unbiased and ethical decisions that will benefit everyone. However, this is not always the case; issues arise during the data prepara
Externí odkaz:
http://arxiv.org/abs/2111.03984
Automatic extraction of product attribute values is an important enabling technology in e-Commerce platforms. This task is usually modeled using sequence labeling architectures, with several extensions to handle multi-attribute extraction. One line o
Externí odkaz:
http://arxiv.org/abs/2106.02318
Data scientists are constantly creating methods to efficiently and accurately populate big data sets for use in large-scale applications. Many recent efforts utilize crowd-sourcing and textual interfaces. In this paper, we propose a new method of cur
Externí odkaz:
http://arxiv.org/abs/1907.00146
Rapid urbanization burdens city infrastructure and creates the need for local governments to maximize the usage of resources to serve its citizens. Smart city projects aim to alleviate the urbanization problem by deploying a vast amount of Internet-o
Externí odkaz:
http://arxiv.org/abs/1905.05633
Autor:
DeHart, Jasmine, Grant, Christan
With the growth and accessibility of mobile devices and internet, the ease of posting and sharing content on social media networks (SMNs) has increased exponentially. Many users post images that contain "privacy leaks" regarding themselves or someone
Externí odkaz:
http://arxiv.org/abs/1806.08471
Traditional data mining algorithms are exceptional at seeing patterns in data that humans cannot, but are often confused by details that are obvious to the organic eye. Algorithms that include humans "in-the-loop" have proved beneficial for accuracy
Externí odkaz:
http://arxiv.org/abs/1712.00715
Social media data provides propitious opportunities for public health research. However, studies suggest that disparities may exist in the representation of certain populations (e.g., people of lower socioeconomic status). To quantify and address the
Externí odkaz:
http://arxiv.org/abs/1710.11048