Discovering Data Structures
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Discovering Data Structures: Nearest Neighbor Search and Beyond
arXiv:2411.03253v2 Announce Type: replace Abstract: We propose a general framework for end-to-end learning of data structures. Our framework adapts to the underlying data distribution and provides fine-grained control over query and space complexity. Crucially, the data structure is learned from scratch, and does not require careful initialization or seeding with candidate data structures/algorithms.
Scientists discover vast hidden structure beneath Antarctica’s ice
Scientists discover vast hidden structure beneath Antarctica’s ice - Date: - June 4, 2026 - Source: - Durham University - Summary: - A giant fan-shaped network of hidden basins has been discovered beneath East Antarctica, revealing that several well-known subglacial features are actually part of one massive geological structure. The finding sheds new light on Antarctica’s ancient tectonic history and could help scientists better understand how the ice sheet behaves today. Researchers have...
Scientists discover giant, fan-shaped structure deep beneath the East Antarctic Ice Sheet
Scientists discover giant, fan-shaped structure deep beneath the East Antarctic Ice Sheet A mysterious geological structure that resembles a human hand with outstretched fingers has been revealed beneath East Antarctica. The discovery shows the frozen continent still hides many geological secrets. Scientists have discovered a giant, fan-shaped structure that connects several well-known basins deep beneath the East Antarctic Ice Sheet — and it may have formed in the breakup of the ancient...
AnchorSteer: Self-Discovered Concept Injection for Structure-Preserving Music Editing
arXiv:2605.31053v1 Announce Type: new Abstract: Controllable music editing is to modify high-level attributes while strictly preserving rhythmic and melodic structures. However, this task is challenged by a semantic-structural entanglement: steering methods often degrade structure to achieve editing performance, while structural adaptors suppress semantic responsiveness. We propose AnchorSteer, a framework that disentangles this tension by coupling structural anchoring with self-discovered...
Evaluating and Learning Robust Bandit Policies Under Uncertain Causal Mechanisms
Announce Type: replace Abstract: Causal graphical models can encode large amounts structural knowledge, both from the background knowledge of domain experts and the structural knowledge discovered from randomized experiments or observational data. However, though we may know the general structure of causal relationships, we often do not know the exact causal mechanisms. In this work, we propose a causal multi-armed bandit evaluation and learning algorithm that can reason effectively despite...
Discovering and decoding latent mean-field structure with variational autoencoders
arXiv:2606.08694v1 Announce Type: cross Abstract: Generative models are increasingly used to capture correlations in many-body systems, but the representations they learn remain largely opaque to physical interpretation. Here, we establish an intuitive criterion that quantifies the capacity of a variational autoencoder (VAE) to faithfully reconstruct the joint probability distribution of a many body system. In a nutshell, a bound on the VAE capacity is obtained by comparing the rate of the...
Restartable Sequences
May 31st, 2026 @ justine's web page The best kept secret at the frontier of system programming right now is the Linux 4.18+ (c. 2018) concept of restartable sequences or rseq for short. They allow you to create thread-safe data structures without locks or atomics which scale to microprocessors with many cores. It's currently only possible to use rseq on Linux using handwritten assembly code.
How I Get Free Traffic from ChatGPT in 2025 (AIO vs SEO)
Three weeks ago, I tested something that completely changed how I think about organic traffic. I opened ChatGPT and asked a simple question: "What's the best course on building SaaS with WordPress?" The answer that appeared stopped me cold.
Executable Schema Contracts: From Automatic Ingestion to Multi-Source Retrieval
arXiv:2606.05415v1 Announce Type: new Abstract: Real-world data spans tables, documents, and semi-structured files with implicit semantics. Querying this data requires integrating evidence across inconsistent schemas and formats, yet existing approaches either demand costly manual engineering or bypass structure entirely.
PyCC.id: A package for hypothesis-driven equation discovery with structural identifiability
Announce Type: new Abstract: Data-driven equation discovery is fundamentally an inverse problem that seeks to infer the governing differential equations of a system directly from time-series measurements. A known issue is the ill-conditioned nature of the inverse problem, which frequently produces multiple mathematical models that fit the data similarly well. One path to address this issue is by incorporating known hypotheses and constraints into the training phase beforehand.