In the dynamic field of genomics, understanding the causal connections between biological variables is pivotal for advancing personalized healthcare. This research presents an innovative method for causal inference in...
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This paper introduces a novel approach to improving the training stability of self-supervised learning (SSL) methods by leveraging a nonparametric memory of seen concepts. The proposed method involves augmenting a neu...
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This paper introduces a novel approach to improving the training stability of self-supervised learning (SSL) methods by leveraging a nonparametric memory of seen concepts. The proposed method involves augmenting a neural network with a memory component to stochastically compare current image views with previously encountered concepts. Additionally, we introduce stochastic memory blocks to regularize training and enforce consistency between image views. We extensively benchmark our method on many vision tasks, such as linear probing, transfer learning, low-shot classification, and image retrieval on many datasets. The experimental results consolidate the effectiveness of the proposed approach in achieving stable SSL training without additional regularizers while learning highly transferable representations and requiring less computing time and resources. Code at https://***/sthalles/MaSSL. Copyright 2024 by the author(s)
In-context learning methods are commonly employed as inference strategies, where Large Language Models (LLMs) are elicited to solve a task by leveraging provided demonstrations without requiring parameter updates. Amo...
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The Non-myth of the Noble Red is a tangible narrative that combines cardboard puppets with digital storytelling in an integrated physical storyworld. This narrative employs networked microcontrollers within the puppet...
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Efficient utilization of Big data in smart cities is crucial for smooth operation of urban environments. Machine learning-enabled big data analytics is essential for optimizing city operations, improving resource mana...
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In this paper, we propose a Thompson Sampling based sequential block elimination approach for dynamic pricing within pure-exploration Multi-Armed Bandit (MAB) setting. Given an l-dimensional action space, which repres...
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Protein-protein interactions (PPIs) are crucial for various cellular activities and disease development, and modulating PPIs using small molecule inhibitors (PPIIs) has gradually become a promising therapeutic strateg...
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Bias detection and mitigation is an active area of research in machine learning. This work extends previous research done by the authors Van Busum and Fang (Proceedings of the 38th ACM/SIGAPP Symposium on Applied Comp...
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In this work, we studied some quantum algorithms, and selected Grover search problem, it will then receive an in-depth analysis of how the problem works and how it can be adapted to its process in a quantum computer, ...
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Analyzed is a new approach to the use of enumeration procedures for calculation of definite multiple integrals. It is shown that the effectiveness of this approach depends on the following factors: on requirements for...
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