On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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10 results for “Birch”

BETULA: Numerically Stable CF-Trees for BIRCH Clusteringcs.LG

Improved BIRCH clustering method to avoid numeric issues.

problem Numeric instability in BIRCH clustering.

method Introduced a new cluster feature to replace the sum of squares, avoiding catastrophic cancellation.

result The new method is more numerically stable and efficient.

BIRCH clustering numeric stability CF-Tree catastrophic cancellation data stream

2020-06-23abs ↗pdf ↗

Automated learning with a probabilistic programming language: Birchstat.ML

Birch automates probabilistic modeling using a Turing-complete language.

problem Automating the matching of probabilistic models with inference methods.

method Formally describes models as programs, revealing structure and form dynamically.

result Probabilistic programming languages can tailor inference methods based on model structure and form.

probabilistic programming automated inference Birch probabilistic modeling conditional dependencies

2018-10-02abs ↗pdf ↗

Machine Learning meets Number Theory: The Data Science of Birch-Swinnerton-Dyermath.NT

Data science reveals patterns in elliptic curve ranks and coefficients.

problem Understanding rational points on elliptic curves via BSD conjecture.

method Data science, machine learning, topological data analysis.

result Patterns and distributions in rank versus Weierstrass coefficients.

elliptic curves Birch-Swinnerton-Dyer conjecture data science machine learning topological data analysis

2019-11-04abs ↗pdf ↗

Murmurations: a case study in AI-assisted mathematicsmath.NT

New arithmetic phenomenon 'murmurations' detected using AI.

problem Detecting new arithmetic patterns in large datasets.

method Machine learning interpretability tools (PCA, saliency, convolutional filters).

result Murmurations encode Frobenius traces and connect to number theory.

murmurations arithmetic statistics Frobenius traces Birch-Swinnerton-Dyer random matrix theory

2026-03-10abs ↗pdf ↗

Machine Learning Approaches to the Shafarevich-Tate Group of Elliptic Curvesmath.NT

Machine learning predicts Shafarevich-Tate group orders of elliptic curves.

problem Predicting the order of the Shafarevich-Tate group of elliptic curves.

method Train feed-forward neural network and regression models on elliptic curve invariants.

result Models achieve high accuracy (

> 0.9

) and predict orders not seen during training.

Machine Learning Elliptic Curves Shafarevich-Tate Group Birch-Swinnerton-Dyer Conjecture LMFDB

2024-12-24abs ↗pdf ↗

Data Aggregation for Hierarchical Clusteringstat.ML

Data aggregation improves HAC for resource-constrained systems.

problem Resource constraints in embedded systems limit HAC's applicability.

method Data aggregation with BETULA algorithm reduces memory and runtime requirements.

result HAC can be applied to large datasets on resource-constrained systems.

Hierarchical Clustering Data Aggregation BIRCH Resource Constraints Embedded Systems

2023-09-05abs ↗pdf ↗

Machine Learning Based Prediction and Classification of Computational Jobs in Cloud Computing Centerscs.LG

Predicts and classifies computational jobs for efficient resource allocation in cloud centers.

problem Efficiently scheduling and assigning resources to computational jobs in cloud centers.

method Applied LSTM neural network for job arrival prediction and BIRCH clustering for job classification.

result Improved accuracy in predicting and classifying computational jobs compared to existing methods.

cloud computing job scheduling resource allocation machine learning LSTM

2019-03-09abs ↗pdf ↗

Clustering with minimum spanning trees: How good can it be?stat.ML

MSTs provide a fast and meaningful clustering method in low-dimensional data.

problem Quantifying the effectiveness of MSTs in low-dimensional clustering tasks.

method Identifying upper bounds for MST performance, reviewing and extending existing MST-based partitioning schemes.

result MST methods can be very competitive, often outperforming traditional clustering algorithms.

minimum spanning trees clustering partitional data K-means Gaussian mixtures

2023-03-10abs ↗pdf ↗

SPINEX-Clustering: Similarity-based Predictions with Explainable Neighbors Exploration for Clustering Problemscs.LG

SPINEX improves clustering with explainable neighbors, outperforming other methods.

problem Improving clustering performance and explainability.

method Leverages similarity and higher-order interactions for clustering.

result SPINEX outperforms 13 clustering algorithms across various datasets.

clustering explainable neighbor exploration similarity-based higher-order interactions

2024-07-09abs ↗pdf ↗

Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programsstat.ML

We introduce a dynamic mechanism for the solution of analytically-tractable substructure in probabilistic programs, using conjugate priors and affine transformations to reduce variance in Monte Carlo estimators. For inference with Sequential Monte Carlo, this automatically yields improvements such as locally-optimal pr…

2017-08-25abs ↗pdf ↗