SHIVAM SAHNI 18110159 | Indian Institute of Technology Gandhinagar (original) (raw)
Computer Science Undergraduate @ IIT Gandhinagar
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Graduate Center of the City University of New York
Galgotias College of Engineering and Technology Greater Noida
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Papers by SHIVAM SAHNI 18110159
5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD)
5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD)
ArXiv, 2021
Recent technological advancements have resulted in a surge in online trading, raising severe conc... more Recent technological advancements have resulted in a surge in online trading, raising severe concerns about theft and fraud, especially on platforms like Bitcoin OTC (over-the-counter), where users’ identities remain anonymous. To mitigate the risk, it has become essential to capture the reputation of users based on their trade histories. The who-trusts-whom signed network of people has the capability to reflect the nature of such positive and negative relations between the users. It can be used to analyze linkage patterns, strength, and resiliency of such platforms. Due to the dynamic nature of trust between individuals, these trust networks are often vulnerable to link or node failures, making it critical to understand the stability of such systems. In this paper, we consider the problem of quantifying the resiliency of signed networks with the help of trustworthy community structures. We propose a metric for computing the Trustworthiness of a community structure. Using the trustw...
ArXiv, 2021
Image Inpainting is one of the very popular tasks in the field of image processing with broad app... more Image Inpainting is one of the very popular tasks in the field of image processing with broad applications in computer vision. In various practical applications, images are often deteriorated by noise due to the presence of corrupted, lost or undesirable information. There have been various restoration techniques used in the past with both classical [1] [2] and deep learning approach for handling such issues [3] . Some traditional methods include image restoration by filling gap pixels using the nearby known pixels or using the moving average over the same. The aim of this project is to perform image inpainting using robust deep learning methods that use partial convolution layers.
5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD)
5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD)
ArXiv, 2021
Recent technological advancements have resulted in a surge in online trading, raising severe conc... more Recent technological advancements have resulted in a surge in online trading, raising severe concerns about theft and fraud, especially on platforms like Bitcoin OTC (over-the-counter), where users’ identities remain anonymous. To mitigate the risk, it has become essential to capture the reputation of users based on their trade histories. The who-trusts-whom signed network of people has the capability to reflect the nature of such positive and negative relations between the users. It can be used to analyze linkage patterns, strength, and resiliency of such platforms. Due to the dynamic nature of trust between individuals, these trust networks are often vulnerable to link or node failures, making it critical to understand the stability of such systems. In this paper, we consider the problem of quantifying the resiliency of signed networks with the help of trustworthy community structures. We propose a metric for computing the Trustworthiness of a community structure. Using the trustw...
ArXiv, 2021
Image Inpainting is one of the very popular tasks in the field of image processing with broad app... more Image Inpainting is one of the very popular tasks in the field of image processing with broad applications in computer vision. In various practical applications, images are often deteriorated by noise due to the presence of corrupted, lost or undesirable information. There have been various restoration techniques used in the past with both classical [1] [2] and deep learning approach for handling such issues [3] . Some traditional methods include image restoration by filling gap pixels using the nearby known pixels or using the moving average over the same. The aim of this project is to perform image inpainting using robust deep learning methods that use partial convolution layers.