Most studies on causal inference tackle the issue of confounding bias by reducing the distribution shift between the control and treated groups. However, it remains an open question to adopt an appropriate metric for ...
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Most studies on causal inference tackle the issue of confounding bias by reducing the distribution shift between the control and treated groups. However, it remains an open question to adopt an appropriate metric for distribution shift in practice. In this paper, we define a generic balancing error on reweighted samples to characterize the confounding bias, and study the connection between the balancing error and the Wasserstein discrepancy derived from the theory of optimal transport. We not only regard the Wasserstein discrepancy as the metric of distribution shift, but also explore the association between the balancing error and the underlying cost function involved in the Wasserstein discrepancy. Motivated by this, we propose to reduce the balancing error under the framework of optimal transport with learnable marginal distributions and the cost function, which is implemented by jointly learning weights and representations associated with factual outcomes. The experiments on both synthetic and real-world datasets demonstrate the effectiveness of our proposed method. Copyright 2024 by the author(s)
Nowadays, the amount of data in image retrieval databases is increasing, which faces great challenges in retrieval time and storage cost. Therefore, image retrieval methods based on hash have attracted extensive atten...
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Thermal sensation is the subjective perception of the human body to its own thermal state, which can accurately reflect the change of human body temperature. In sports, human thermal sensation is an important psycholo...
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The purpose of image stitching is to generate a panoramic image with a large viewing angle from a series of images. Panoramic images can be applied to many practical scenes, such as military, simulation, augmented rea...
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The proliferation of Automated Teller Machines (ATMs) in the banking sector has raised the stakes in identifying the most suitable locations for these machines, given their impact on the profitability and satisfaction...
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As a distributed ledger technology, blockchain has broad applications in many areas such as finance, agriculture, and contract signing due to its advantages of being tamperproof and difficult to forge. However, the op...
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Gene expression profiles play a significant role in drug research. If the gene expression profile under the action of drugs can be obtained quickly, such as through computational methods, the analysis of the relations...
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Heterogeneous Information Networks(HINs)contain multiple types of nodes and edges;therefore,they can preserve the semantic information and structure *** analysis using an HIN has obvious advantages over a transformati...
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Heterogeneous Information Networks(HINs)contain multiple types of nodes and edges;therefore,they can preserve the semantic information and structure *** analysis using an HIN has obvious advantages over a transformation into a homogenous information network,which can promote the clustering results of different types of *** our study,we applied a Nonnegative Matrix Tri-Factorization(NMTF)in a cluster analysis of multiple metapaths in *** the parameter estimation method of the probability distribution in previous studies,NMTF can obtain several dependent latent variables simultaneously,and each latent variable in NMTF is associated with the cluster of the corresponding node in the *** method is suited to co-clustering leveraging multiple metapaths in HIN,because NMTF is employed for multiple nonnegative matrix factorizations simultaneously in our *** results on the real dataset show that the validity and correctness of our method,and the clustering result are better than that of the existing similar clustering algorithm.
Facial expression recognition (FER) is a challenging task. The following two significant problems often exist in real-life FER tasks: first, facial expression images in the wild are uncertain, i.e., occlusion or blurr...
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Existing deep interactive segmentation methods only focus on the extraction of specific instance objects. When the target of interest to users is a category, existing methods have to perform more interactions. We take...
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