Estimating Network-Mediated Causal Effects via Principal Components Network Regression

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Selective Inference with Distributed Data

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Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization

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An Axiomatic Definition of Hierarchical Clustering

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Test-Time Training on Video Streams

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Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback

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A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation

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Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents

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Enhancing Graph Representation Learning with Localized Topological Features

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Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization

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DisC2o-HD: Distributed causal inference with covariates shift for analyzing real-world high-dimensional data

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Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes

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Efficiently Escaping Saddle Points in Bilevel Optimization

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CAN ARTIFICIAL INTELLIGENCE PREDICT A TSUNAMI?

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BIELIK 7B V0.1: POLISH LANGUAGE MODEL - DEVELOPMENT, INSIGHTS, AND EVALUATION

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FL-MEC: FEDERATED LEARNING FOR NETWORK TRAFFIC CLASSIFICATION ON THE NETWORK EDGE

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PRELIMINARY STUDY ON ARTIFICIAL INTELLIGENCE METHODS FOR CYBERSECURITY THREAT DETECTION INCOMPUTER NETWORKS BASED ON RAWDATA PACKETS

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CHARACTERISTIC SKY BACKGROUND FEATURES AROUND GALAXY MERGERS

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DEVELOPING ARTIFICIAL INTELLIGENCE IN THE CLOUD: THE AI INFN PLATFORM

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A NETWORK-BASED COMPUTATIONALPIPELINE TO STUDY THE VARIABILITY OFTRANSCRIPTOME PROFILES FOR HUMANDISEASES

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