Many real world applications employ multi-variate performance measures and each example can belong to multiple classes. The currently most popular approaches train an SVM for each class, followed by ad hoc thresholding. Probabilistic models using Bayesian decision theory are also commonly adopted. In this paper, we propose a Bayesian online multi-label classification framework (BOMC) which learns a probabilistic linear classifier. The likelihood is modeled by a graphical model similar to TrueSkill$^text{TM}$, and inference is based on Gaussian density […]

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The 66th Annual Symposium on Foundations of Computer Science (FOCS 2025), sponsored by the IEEE Computer Society Technical Committee on Mathematical Foundations of Computing, will be held in Sydney, Australia, December 14-17. Papers presenting new and original research on theory of computation are sought. Typical but not exclusive topics of interest include: algorithmic coding theory, algebraic computation, algorithmic graph theory, algorithmic game theory, algorithms and data structures, analysis of Boolean functions, approximation algorithms, average-case complexity, computational applications of logic, […]

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Key Highlights: What Is CES and Why It Matters CES (Consumer Electronics Show) is one of the world’s most influential technology events, held annually in Las Vegas. Taking place from January 6–9, 2026. The show is widely seen as a barometer for where consumer and enterprise technology is headed. Over the decades, CES has served as the launchpad for technologies that later entered mainstream use, from home video systems to electric vehicles. CES 2026 is shaping up to […]

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Networks are becoming a unifying framework for modeling complex systems and network inference problems are frequently encountered in many fields. Here, I develop and apply a generative approach to network inference (RCweb) for the case when the network is sparse and the latent (not observed) variables affect the observed ones. From all possible factor analysis (FA) decompositions explaining the variance in the data, RCweb selects the FA decomposition that is consistent with a sparse underlying network. The sparsity […]

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arXiv:2510.10968v2 Announce Type: replace-cross Abstract: Derivative-free Bayesian inversion is an important task in many science and engineering applications, particularly when computing the forward model derivative is computationally and practically challenging. In this paper, we introduce Blade, which can produce accurate and well-calibrated posteriors for Bayesian inversion using an ensemble of interacting particles. Blade leverages powerful data-driven priors based on diffusion models, and can handle nonlinear forward models that permit only black-box access (i.e., derivative-free). Theoretically, we establish a […]

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President Javier Milei’s clear victory on Sunday, October 26, over the opposition in the midterm elections, where he obtained almost 41% of the vote to 31% of the Peronists, was greeted with market euphoria.

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A new approach to regression regularization called the Pairwise Elastic Net is proposed. Like the Elastic Net, it simultaneously performs automatic variable selection and continuous shrinkage. In addition, the Pairwise Elastic Net encourages the grouping of strongly correlated predictors based on a pairwise similarity measure. We give examples of how the Pairwise Elastic Net can be used to achieve the objectives of Ridge regression, the Lasso, the Elastic Net, and Group Lasso. Finally, we present a coordinate descent […]

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Adding breadcrumbs to a website seems like an easy task and honestly, it should be. Unfortunately it’s not, unless you want to end up copying the almost-same code in all your pages. Today I’ll be talking about how to add and manage breadcrumbs in an ASP.NET Core website using SmartBreadcrumbs (1.

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