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This AI Paper Proposes Two Types of Convolution, Pixel Difference Convolution (PDC) and Binary Pixel Difference Convolution (Bi-PDC), to Enhance the Representation Capacity of Convolutional Neural Network CNNs

AI NewsFebruary 13, 2024128Views0Likes0Comments
Deep convolutional neural networks (DCNNs) have been a game-changer for several computer vision tasks. These include object identification, object recognition, image segmentation, and edge detection. The ever-growing size and power consumption of DNNs have been key to enabling much of this advancement. Embedded, wearable, and Internet of Things (IoT) devices, which have restricted computing resources…

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Sensitivity Analysis for Unobserved Confounding | by Ugur Yildirim | Feb, 2024

Data ScienceFebruary 13, 2024137Views0Likes0Comments
How to know the unknowable in observational studies Introduction Problem Setup 2.1. Causal Graph 2.2. Model With and Without Z 2.3. Strength of Z as a Confounder Sensitivity Analysis 3.1. Goal 3.2. Robustness Value PySensemakr Conclusion Acknowledgements References The specter of unobserved confounding (aka omitted variable bias) is a notorious problem in observational studies. In…

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Synthetic Data for Machine Learning

Data AnalyticsFebruary 12, 2024131Views0Likes0Comments
It’s no secret that supervised machine learning models need to be trained on high-quality labeled datasets. However, collecting enough high-quality labeled data can be a significant challenge, especially in situations where privacy and data availability are major concerns. Fortunately, this problem can be mitigated with synthetic data. Synthetic data is data that is artificially generated…

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Advancing Vision-Language Models: A Survey by Huawei Technologies Researchers in Overcoming Hallucination Challenges

AI NewsFebruary 12, 2024149Views0Likes0Comments
The emergence of Large Vision-Language Models (LVLMs) characterizes the intersection of visual perception and language processing. These models, which interpret visual data and generate corresponding textual descriptions, represent a significant leap towards enabling machines to see and describe the world around us with nuanced understanding akin to human perception. A notable challenge that impedes their…

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Pinterest Researchers Present an Effective Scalable Algorithm to Improve Diffusion Models Using Reinforcement Learning (RL)

AI NewsFebruary 12, 2024138Views0Likes0Comments
Diffusion models are a set of generative models that work by adding noise to the training data and then learn to recover the same by reversing the noising process. This process allows these models to achieve state-of-the-art image quality, making them one of the most significant developments in Machine Learning (ML) in the past few…

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