arXiv:2501.10538v2 Announce Type: replace-cross Abstract: The practical success of deep learning has led to the discovery of several surprising phenomena. One of these phenomena, that has spurred intense theoretical research, is “benign overfitting”: deep neural networks seem to generalize well in the over-parametrized regime even though the networks show a perfect fit to noisy training data. It is now known that benign overfitting also occurs in various classical statistical models. For linear maximum margin classifiers, benign overfitting has […]

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Pioneering Predictive Intelligence: How One Architect Transformed Manufacturing Asset Management Through IoT and Oracle Cloud Innovation In an era where unplanned downtime can cost manufacturers millions and operational resilience determines market leadership, the convergence of IoT technology with enterprise asset management represents a paradigm shift in how organizations approach maintenance intelligence. The groundbreaking IoT-enabled predictive maintenance solution architected by Ramachandra Handaragal stands as a watershed moment in manufacturing operations—the industry’s first fully integrated IoT-Oracle eAM platform that transformed […]

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arXiv:2510.08102v2 Announce Type: replace-cross Abstract: Tokenization — the process of decomposing a given text into a sequence of subwords called tokens — is one of the key components in the development of language models. Particularly, auto-regressive language models generate texts token by token, i.e., by predicting the next-token distribution given the previous ones, and thus tokenization directly affects their efficiency in text generation. Since each language model has their own vocabulary as a set of possible tokens, they […]

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In this paper we consider a regularization approach to variable selection when the regression function depends nonlinearly on a few input variables. The proposed method is based on a regularized least square estimator penalizing large values of the partial derivatives. An efficient iterative procedure is proposed to solve the underlying variational problem, and its convergence is proved. The empirical properties of the obtained estimator are tested both for prediction and variable selection. The algorithm compares favorably to more […]

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arXiv:2506.16965v3 Announce Type: replace-cross Abstract: Ensemble learning remains a cornerstone of machine learning, with stacking used to integrate predictions from multiple base learners through a meta-model. However, deep stacking remains uncommon due to feature redundancy, complexity, and computational burden. To address these limitations, RocketStack is introduced as a level-aware recursive stacking architecture explored up to ten stacking levels, extending beyond prior architectures. At level 1, base-learner predictions are fused with original features; at later levels, weaker learners are […]

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arXiv:2602.06079v1 Announce Type: new Abstract: The scaling of Large Language Models (LLMs) drives interest in matrix-based optimizers (e.g., Shampoo, Muon, SOAP) for their convergence efficiency; yet their requirement for holistic updates conflicts with the tensor fragmentation in distributed frameworks like Megatron. Existing solutions are suboptimal: synchronous approaches suffer from computational redundancy, while layer-wise partitioning fails to reconcile this conflict without violating the geometric constraints of efficient communication primitives. To bridge this gap, we propose Canzona, a Unified, Asynchronous, […]

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Working extensively with AWS credentials in Kubernetes this quarter revealed how often credential precedence causes configuration issues. While the AWS SDK’s credential chain is well-designed, understanding the priority order is crucial for production deployments. Here’s what I’ve learned. The Problem Nobody Talks About A recent incident illustrated this well: We configured IRSA for a microservice, validated it in staging, and deployed to production successfully. Two weeks later, an audit revealed the service was using broader IAM permissions than […]

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The previous post introduced the idea of finding your location by sighting a star. There is some point on Earth that is directly underneath the star at any point in time, and that location is called the star’s GP (geographic position). That is one vertex of the navigational triangle. The other two vertices are your position and the North Pole. Unless you’re at Santa’s workshop and observing a star nearly directly overhead, the navigational triangle is a big […]

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arXiv:2602.06061v1 Announce Type: new Abstract: Relays are pivotal in military communication networks, expanding coverage and ensuring reliable connectivity in challenging operational environments. While traditional terrestrial relays (TR) are constrained by fixed locations and vulnerability to physical obstructions, unmanned aerial vehicle (UAV)-mounted aerial relays (AR) offer a dynamic and flexible alternative by operating above obstacles and adapting to changing battlefield conditions. This paper provides a comprehensive survey of AR systems in military communications, presenting a detailed comparison between AR […]

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