Machine Learning
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[2508.21618] Physics-Informed Spectral Modeling for Hyperspectral Imaging
Abstract page for arXiv paper 2508.21618: Physics-Informed Spectral Modeling for Hyperspectral Imaging
[2508.13657] In-Context Decision Making for Optimizing Complex AutoML Pipelines
Abstract page for arXiv paper 2508.13657: In-Context Decision Making for Optimizing Complex AutoML Pipelines
[2508.07299] Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning
Abstract page for arXiv paper 2508.07299: Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-...
[2508.05423] Negative Binomial Variational Autoencoders for Overdispersed Latent Modeling
Abstract page for arXiv paper 2508.05423: Negative Binomial Variational Autoencoders for Overdispersed Latent Modeling
[2411.02622] Pseudo-Probability Unlearning: Efficient and Privacy-Preserving Machine Unlearning
Abstract page for arXiv paper 2411.02622: Pseudo-Probability Unlearning: Efficient and Privacy-Preserving Machine Unlearning
[2503.02129] Path Regularization: A Near-Complete and Optimal Nonasymptotic Generalization Theory for Multilayer Neural Networks and Double Descent Phenomenon
Abstract page for arXiv paper 2503.02129: Path Regularization: A Near-Complete and Optimal Nonasymptotic Generalization Theory for Multil...
[2410.17473] DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning
Abstract page for arXiv paper 2410.17473: DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning
[2409.01633] SleepNet and DreamNet: Enriching and Reconstructing Representations for Consolidated Visual Classification
Abstract page for arXiv paper 2409.01633: SleepNet and DreamNet: Enriching and Reconstructing Representations for Consolidated Visual Cla...
[2405.16240] AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models
Abstract page for arXiv paper 2405.16240: AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models
[2405.11619] Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detection
Abstract page for arXiv paper 2405.11619: Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detection
[2307.03571] Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization
Abstract page for arXiv paper 2307.03571: Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametri...
[2306.02781] An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures, Protocols, and Applications
Abstract page for arXiv paper 2306.02781: An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures...
[2604.07350] Fast Spatial Memory with Elastic Test-Time Training
Abstract page for arXiv paper 2604.07350: Fast Spatial Memory with Elastic Test-Time Training
[2604.07343] Personalized RewardBench: Evaluating Reward Models with Human Aligned Personalization
Abstract page for arXiv paper 2604.07343: Personalized RewardBench: Evaluating Reward Models with Human Aligned Personalization
[2604.07323] Gaussian Approximation for Asynchronous Q-learning
Abstract page for arXiv paper 2604.07323: Gaussian Approximation for Asynchronous Q-learning
[2604.07286] CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency
Abstract page for arXiv paper 2604.07286: CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency
[2604.07282] Are Face Embeddings Compatible Across Deep Neural Network Models?
Abstract page for arXiv paper 2604.07282: Are Face Embeddings Compatible Across Deep Neural Network Models?
[2604.07276] Making Room for AI: Multi-GPU Molecular Dynamics with Deep Potentials in GROMACS
Abstract page for arXiv paper 2604.07276: Making Room for AI: Multi-GPU Molecular Dynamics with Deep Potentials in GROMACS
[2604.07274] A Systematic Study of Retrieval Pipeline Design for Retrieval-Augmented Medical Question Answering
Abstract page for arXiv paper 2604.07274: A Systematic Study of Retrieval Pipeline Design for Retrieval-Augmented Medical Question Answering
[2604.07267] The Theory and Practice of Highly Scalable Gaussian Process Regression with Nearest Neighbours
Abstract page for arXiv paper 2604.07267: The Theory and Practice of Highly Scalable Gaussian Process Regression with Nearest Neighbours
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