arXiv:2602.23587v1 Announce Type: new Abstract: Knowledge distillation transfers large teacher models to compact student models, enabling deployment on resource-limited platforms while suffering minimal performance degradation. However, this paradigm could lead to various security risks, especially model theft. Existing defenses against model theft, such as watermarking and secure enclaves, focus primarily on identity authentication and incur significant resource costs. Aiming to provide post-theft accountability and traceability, we propose a novel fingerprinting framework that superimposes device-specific Physical Unclonable Function (PUF) […]

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arXiv:2507.17544v3 Announce Type: replace Abstract: Differential privacy has become a cornerstone in the development of privacy-preserving learning algorithms. This work addresses optimizing differentially private kernel learning within the empirical risk minimization (ERM) framework. We propose a novel differentially private kernel ERM algorithm based on random projection in the reproducing kernel Hilbert space using Gaussian processes. Our method achieves minimax-optimal excess risk for both the squared loss and Lipschitz-smooth convex loss functions under a local strong convexity condition. We […]

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The rapid expansion of online shopping has increased the demand for timely parcel delivery, compelling logistics service providers to enhance the efficiency, agility, and predictability of their hub networks. In order to solve the problem, we propose a novel deep learning-based ensemble framework that leverages historical arrival patterns and real-time parcel status updates to forecast upcoming workloads at logistic hubs. This approach not only facilitates the generation of short-term forecasts, but also improves the accuracy of future hub […]

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This article was co-published with STAT, a national publication that delivers trusted and authoritative journalism about health, medicine, and the life sciences. Sign up for its health tech newsletter here. Telehealth company Cerebral will limit the consumer health data it uses for advertising purposes under a new order announced by the Federal Trade Commission last week. Cerebral, a startup best known for dispensing counseling services and prescriptions for conditions like anxiety and depression, has also agreed to pay $7 million […]

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arXiv:2603.05581v1 Announce Type: new Abstract: Urban traffic flow is governed by the complex, nonlinear interaction between land use configuration and spatiotemporally heterogeneous mobility demand. Conventional global regression and time-series models cannot simultaneously capture these multi-scale dynamics across multiple travel modes. This study proposes a GeoAI Hybrid analytical framework that sequentially integrates Multiscale Geographically Weighted Regression (MGWR), Random Forest (RF), and Spatio-Temporal Graph Convolutional Networks (ST-GCN) to model the spatiotemporal heterogeneity of traffic flow patterns and their interaction with […]

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Product teams spend enormous energy getting to launch. We know the drill—roadmaps debated for weeks, specs refined until everyone’s sick of looking at them, designs polished to pixel-perfect precision. Metrics get defined, redefined, and argued over. Finally, you ship, and the whole team exhales. That’s usually when the real work should start. Because the hardest part of product management isn’t shipping. It’s listening honestly to what happens after—and being willing to act on what you hear, even when […]

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Disclaimer While working as a project manager, I often heard comments like: “Why do we even need PMs? What do they actually do? They only talk and nothing more.” It’s a fairly common opinion. So I prepared an article about what PM can actually do (together with their team) and how impactful that work can be for a project. As we PMs and producers love — with numbers, tables and charts. There are three part about Art Pipeline, […]

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arXiv:2602.06211v1 Announce Type: new Abstract: Accurate 3D pose estimation of drones is essential for security and surveillance systems. However, existing methods often rely on prior drone information such as physical sizes or 3D meshes. At the same time, current datasets are small-scale, limited to single models, and collected under constrained environments, which makes reliable validation of generalization difficult. We present DroneKey++, a prior-free framework that jointly performs keypoint detection, drone classification, and 3D pose estimation. The framework employs […]

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