Machine Learning Engineer: 8th April 2025

Reproducing word2vec with JAX (eli.thegreenplace.net, 2025-04-05). Eli Bendersky reproduces the word2vec model using JAX, focusing on the CBOW architecture, training methodology, data preprocessing, and optimizations for embedding word representations

Using pgvector for timeseries data (cybertec-postgresql.com, 2025-04-03). pgvector enhances PostgreSQL for analyzing timeseries data, enabling anomaly detection through vector mathematics, including handling arrays and using window functions to process historical stock market data effectively

Traditional Backtesting is Outdated. Use CPCV Instead (medium.datadriveninvestor.com, 2025-04-07). Traditional backtesting is criticized for its inherent biases. The CPCV framework offers a robust alternative, utilizing multiple train-test combinations and purging to ensure reliable financial model validation with Python

Diagonalize Matrix for Data Compression with Singular Value Decomposition (pyimagesearch.com, 2025-04-07). Learn to apply Singular Value Decomposition (SVD) for matrix diagonalization and data compression, reducing storage needs while preserving key information through efficient matrix representation

A Tutorial on Meta-Reinforcement Learning (nowpublishers.com, 2025-04-03). Meta-reinforcement learning (meta-RL) methods develop efficient RL algorithms through machine learning, focusing on adapting policies with minimal data across task distributions and addressing data inefficiencies in deep reinforcement learning

Ensembles of Models (datageeek.com, 2025-04-07). An analysis of the BIST Technology Index utilizing ensemble modeling techniques including Auto ARIMA, Prophet, and Elastic Net, with code demonstrating the use of R packages like tidymodels and modeltime

Some experiments to help me understand Neural Nets better, post 2 of N (addxorrol.blogspot.com, 2025-04-05). Exploring the mathematical details of neural networks through an 'origami view' and the concept of a 'polytope lens', using the standard layer equation σ( W x + b )

Chain Rule (leimao.github.io, 2025-04-06). De novo chain rule expression uses Jacobian matrix multiplication to unify univariable and multivariable calculus, providing a more intuitive approach to derivative calculations across different mathematical domains

gradient flow for projected Langevin dynamics (xianblog.wordpress.com, 2025-04-06). Daniel Lacker discusses projected Langevin dynamics, exploring gradient flows for entropy-regularized optimal transport using SDEs, Nadaraya-Watson estimates, and revealing challenges in algorithmic implementation during a seminar at Paris Dauphine

Wasserstein distance for elliptic families (djalil.chafai.net, 2025-04-04). Wasserstein distance calculation for elliptic families using location-scale transformations, covering multivariate Student t distributions and Gaussian distributions with explicit moment-based formulas

A complete characterization of the expressivity of shallow, bias-free ReLU networks (james-simon.github.io, 2025-04-03). Shallow ReLU networks lack expressivity for certain functions, unable to represent odd polynomials or nonzero sore learning of sinusoidal functions despite satisfying the universal approximation theorem under specific conditions

MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage (arxiv:cs, 2025-04-02). MLKV is an open-source disk-based key-value storage framework that optimizes embedding model training, addressing scalability issues and outperforming existing strategies by 1.6-12.6x in real applications like payment transaction risk detection

Accelerating IoV Intrusion Detection: Benchmarking GPU-Accelerated vs CPU-Based ML Libraries (arxiv:cs, 2025-04-02). Research evaluating GPU-accelerated cuML vs CPU-based scikit-learn for IoV intrusion detection shows training time reductions of up to 159 times and prediction speeds improved by up to 95 times while maintaining detection accuracy

Scalable Robust Bayesian Co-Clustering with Compositional ELBOs (arxiv:stat, 2025-04-05). Presents a variational Co-clustering framework using a Gaussian Mixture Model prior, integrates noise handling via Compositional ELBO, and outperforms existing methods in accuracy and robustness on diverse datasets

SOLAR: Scalable Distributed Spatial Joins through Learning-based Optimization (arxiv:cs, 2025-04-02). SOLAR introduces a learning-based optimization approach for scalable distributed spatial joins, improving efficiency by predicting optimal strategies, and achieving up to 3.6X faster join runtime through effective spatial partitioning

Sparsity-Aware Communication for Distributed Graph Neural Network Training (arxiv:cs, 2025-04-07). Sparsity-aware algorithms improve GNN training by communicating only necessary matrix elements, utilizing graph partitioning to reorder matrices, and minimizing communication volume, achieving up to 14X speedup on 256 GPUs