We develop a semi-parametric state-space model for time-series data with latent regime transitions. Classical Markov-switching models use fixed parametric transition functions, such as logistic or probit links, which restrict flexibility when transitions depend on nonlinear and context-dependent effects. We replace this assumption with learned functions $f_0, f_1 in calH$, where $calH$ is either a reproducing kernel Hilbert space or a spline approximation space, and define transition probabilities as $p_{jk,t} = sigmoid(f(bx_{t-1}))$. The transition functions are estimated jointly with […]

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TLS 1.3 zero-round-trip-time (0-RTT) resumption reduces reconnection latency by allowing clients to transmit early application data using pre-shared keys (PSK) derived from previously established session tickets. This mechanism is pivotal for latency-sensitive web services, API gateways, and IoT applications. However, the cryptographic foundations of current session tickets—symmetric keys derived from classical X25519 key exchange—are fundamentally vulnerable to Harvest-Now-Decrypt-Later (HNDL) quantum attacks: an adversary capturing session ticket exchanges today can retroactively decrypt PSKs and all 0-RTT early data once […]

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arXiv:2602.10530v1 Announce Type: new Abstract: Multiview datasets are common in scientific and engineering applications, yet existing fusion methods offer limited theoretical guarantees, particularly in the presence of heterogeneous and high-dimensional noise. We propose Generalized Robust Adaptive-Bandwidth Multiview Diffusion Maps (GRAB-MDM), a new kernel-based diffusion geometry framework for integrating multiple noisy data sources. The key innovation of GRAB-MDM is a {view}-dependent bandwidth selection strategy that adapts to the geometry and noise level of each view, enabling a stable and […]

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In imitation learning, robots are supposed to learn from demonstrations of the desired behavior. Most of the work in imitation learning for swarm robotics provides the demonstrations as rollouts of an existing policy. In this work, we provide a framework based on generative adversarial imitation learning that aims to learn collective behaviors from human demonstrations. Our framework is evaluated across six different missions, learning both from manual demonstrations and demonstrations derived from a PPO-trained policy. Results show that […]

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arXiv:2412.19217v4 Announce Type: replace-cross Abstract: The rapid expansion of citizen science initiatives has led to a significant growth of biodiversity databases, and particularly presence-only (PO) observations. PO data are invaluable for understanding species distributions and their dynamics, but their use in a Species Distribution Model (SDM) is curtailed by sampling biases and the lack of information on absences. Poisson point processes are widely used for SDMs, with Maxent being one of the most popular methods. Maxent maximises the […]

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Release: datasette-ports 0.3 A small update for my tool for helping me figure out what all of the Datasette instances on my laptop are up to. Show working directory derived from each PID Show the full path to each database file Output now looks like this: http://127.0.0.1:8007/ – v1.0a26 Directory: /Users/simon/dev/blog Databases: simonwillisonblog: /Users/simon/dev/blog/simonwillisonblog.db Plugins: datasette-llm datasette-secrets http://127.0.0.1:8001/ – v1.0a26 Directory: /Users/simon/dev/creatures Databases: creatures: /tmp/creatures.db Tags: datasette

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How Blitz scaled their game coaching app with lower latency and leaner operations Blitz is a fast-growing startup that provides personalized coaching for games such as League of Legends, Valorant, and Fortnite. They aim to help gamers become League of Legends legends through real-time insights and post-match analysis. While players play, the app does quite a lot of work. It captures live match data, analyzes it quickly, and uses it for real-time game screen overlays plus personalized post-game coaching. […]

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Introduction When I started exploring Retrieval-Augmented Generation (RAG) systems for incident analysis, I realized that jumping straight into paid APIs like Claude or OpenAI wasn’t practical for learning and experimentation. Instead, I wanted to build something completely local, free to run, and powerful enough to handle real production scenarios. This article documents my journey building a fully functional RAG system that analyzes production incidents by learning from past issues — without spending a dime on API calls. Everything runs on […]

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