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AI Blogs
Integrating Random Effects in Deep Neural Networks The paper “Integrating Random Effects in Deep Neural Networks” by Giora Simchoni and Saharon Rosset (2023) explores the use of mixed models to handle correlated data in deep neural networks (DNNs). While DNNs…
Introducing TurboGP, a Python-based Genetic Programming (GP) library that is exclusively developed for machine learning purposes. TurboGP stands out from other GP implementations by incorporating advanced features like island and cellular population schemes, along with various genetic operations like migration…
Tree-AMP: Compositional Inference with Tree Approximate Message Passing Antoine Baker, Florent Krzakala, Benjamin Aubin, Lenka Zdeborová; 24(57):1−89, 2023. Abstract The python package Tree-AMP is introduced as a tool for compositional inference in high-dimensional tree-structured models. This package offers a comprehensive…
The content discusses the utilization of Integrated Access and Backhauling (IAB) as a cost-effective alternative to fiber-wired links for achieving higher data rates in future networks. The design of such networks presents optimization challenges due to non-convex and combinatorial nature.…
Improved Complexity for Restarted Nonconvex Accelerated Gradient Descent By Huan Li and Zhouchen Lin; 24(157):1−37, 2023. Abstract This paper focuses on accelerated gradient methods for nonconvex optimization problems with Lipschitz continuous gradient and Hessian. We introduce two simple accelerated gradient…
We propose an architecture with input-dependent dynamic depth for processing streaming audio, using a vision-inspired keyword spotting framework. This architecture extends a conformer encoder by adding trainable binary gates, which allow the network to dynamically skip certain modules based on…
Topological Convolutional Layers for Deep Learning Ephy R. Love, Benjamin Filippenko, Vasileios Maroulas, Gunnar Carlsson; 24(59):1−35, 2023. Abstract This article presents the Topological CNN (TCNN), a collection of convolutional methods that are defined topologically. The TCNN utilizes manifolds that have…
Analyzing financial market trends using time series analysis and natural language processing is a complex task due to the multitude of variables that can influence stock prices. These variables include economic and political events, as well as public attitudes. Recent…
New Sequence Results and Improved Algorithmic Guarantees for Asynchronous Iterations in Optimization Authors: Hamid Reza Feyzmahdavian, Mikael Johansson; Published in Journal of Machine Learning Research, 24(158):1−75, 2023. Abstract This paper presents novel convergence results for asynchronous iterations used in the…
arXivLabs is a platform where collaborators can develop and share new features for arXiv directly on our website. Both individuals and organizations that are involved with arXivLabs have embraced and accepted our core values of openness, community, excellence, and user…
