Sampling and Estimation on Manifolds using the Langevin Diffusion

Subjects: “…Artificial Intelligence & Machine Learning…”
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Sharp Bounds for Sequential Federated Learning on Heterogeneous Data

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Local Linear Recovery Guarantee of Deep Neural Networks at Overparameterization

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Stabilizing Sharpness-Aware Minimization Through A Simple Renormalization Strategy

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Fine-Grained Change Point Detection for Topic Modeling with Pitman-Yor Process

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Deletion Robust Non-Monotone Submodular Maximization over Matroids

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Instability, Computational Efficiency and Statistical Accuracy

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Estimation of Local Geometric Structure on Manifolds from Noisy Data

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Ontolearn---A Framework for Large-scale OWL Class Expression Learning in Python

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Continuously evolving rewards in an open-ended environment

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Recursive Causal Discovery

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Evaluation of Active Feature Acquisition Methods for Time-varying Feature Settings

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On Adaptive Stochastic Optimization for Streaming Data: A Newton's Method with O(dN) Operations

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Determine the Number of States in Hidden Markov Models via Marginal Likelihood

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Variance-Aware Estimation of Kernel Mean Embedding

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Scaling ResNets in the Large-depth Regime

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A Comparative Evaluation of Quantification Methods

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Lightning UQ Box: Uncertainty Quantification for Neural Networks

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Scaling Data-Constrained Language Models

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Curvature-based Clustering on Graphs

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