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Animal Movement Models with Mechanistic Selection Functions
A suite of statistical methods are used to study animal movement. Most of these methods treat animal telemetry data in one of three ways: as discrete processes, as continuous processes, or as point processes. We briefly review e ... Read More >
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Variance Reduced Stochastic Proximal Algorithm for AUC Maximization
Stochastic Gradient Descent has been widely studied with classification accuracy as a performance measure. However, these stochastic algorithms cannot be directly used when non-decomposable pairwise performance measures are used ... Read More >
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Convex Hierarchical Clustering for Graph-Structured Data
Convex clustering is a recent stable alternative to hierarchical clustering. It formulates the recovery of progressively coalescing clusters as a regularized convex problem. While convex clustering was originally designed for ha ... Read More >
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Theoretical Guarantees for Model Auditing with Finite Adversaries
Privacy concerns have led to the development of privacy-preserving approaches for learning models from sensitive data. Yet, in practice, even models learned with privacy guarantees can inadvertently memorize unique training exam ... Read More >
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Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Mode ...
Learning generative models that span multiple data modalities, such as vision and language, is often motivated by the desire to learn more useful, generalisable representations that faithfully capture common underlying factors b ... Read More >
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MAP Clustering under the Gaussian Mixture Model via Mixed Integer Nonlinear Opti ...
We present a global optimization approach for solving the maximum a-posteriori (MAP) clustering problem under the Gaussian mixture model.Our approach can accommodate side constraints and it preserves the combinatorial structure ... Read More >
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Deep Transfer Learning for Thermal Dynamics Modeling in Smart Buildings
Thermal dynamics modeling has been a critical issue in building heating, ventilation, and air-conditioning (HVAC) systems, which can significantly affect the control and maintenance strategies. Due to the uniqueness of each spec ... Read More >
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Subspace Clustering with Active Learning
Subspace clustering is a growing field of unsupervised learning that has gained much popularity in the computer vision community. Applications can be found in areas such as motion segmentation and face clustering. It assumes tha ... Read More >
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A multiple testing framework for diagnostic accuracy studies with co-primary end ...
Major advances have been made regarding the utilization of artificial intelligence in health care. In particular, deep learning approaches have been successfully applied for automated and assisted disease diagnosis and prognosis ... Read More >
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Impact of Narrow Lanes on Arterial Road Vehicle Crashes: A Machine Learning Appr ...
In this paper we adopted state-of-the-art machine learning algorithms, namely: random forest (RF) and least squares boosting, to model crash data and identify the optimum model to study the impact of narrow lanes on the safety o ... Read More >