Data Science

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

Scientists uncover new method to generate protein datasets for training AI

6 Months Using AI for Actual Work: What's Incredible, What's Overhyped, and What's Quietly Dangerous

Six months ago I committed to using AI tools for everything I possibly could in my work. Every day, every task, every workflow. Here's th...

[R] LETS Forecast: Learning Embedology for Time Series Forecasting

This article discusses the application of Takens' theorem and Empirical Dynamical Modeling to enhance time series forecasting techniques.

[Hire Us]Full-Stack Dev Team Available – AI/ML, Data Science, UI/UX & End-to-End Execution

A small team of developers offers expertise in AI/ML, data science, and UI/UX for collaborative projects, emphasizing their commitment an...

Is alignment missing a dataset that no one has built yet?

The article discusses the absence of a dataset that captures the unique nuances of human identity, which are not reflected in existing la...

[D] Supervisor support

The article discusses the level of support PhD students in AI receive from their supervisors, focusing on guidance in research output and...

Let’s talk about Ring, lost dogs, and the surveillance state | The Verge

The Verge discusses the backlash against Ring's Search Party feature, which raises concerns about privacy and surveillance following its ...

Fractal Analytics' muted IPO debut signals persistent AI fears in India | TechCrunch

Fractal Analytics, India's first AI company to go public, experienced a lackluster IPO debut, closing down 7% from its issue price amid i...

All the important news from the ongoing India AI Impact Summit | TechCrunch

India's AI Impact Summit gathers leaders from major tech firms and governments to discuss AI investments, innovations, and the future of ...

The scientist using AI to hunt for antibiotics just about everywhere | MIT Technology Review

César de la Fuente is leveraging AI to discover new antibiotics by exploring genetic sequences from various organisms, including extinct ...

[2602.12039] The Implicit Bias of Logit Regularization

The paper explores the implicit bias introduced by logit regularization in classifiers, demonstrating its effects on weight alignment and...

[2602.11454] Adaptive Power Iteration Method for Differentially Private PCA

This paper presents an adaptive power iteration method for computing the top singular vector of a matrix while ensuring differential priv...

[2602.07466] Learned Finite Element-based Regularization of the Inverse Problem in Electrocardiographic Imaging

This article presents a novel framework for regularizing the inverse problem in electrocardiographic imaging by combining spatial and tem...

[2601.22983] PIDSMaker: Building and Evaluating Provenance-based Intrusion Detection Systems

PIDSMaker is an open-source framework designed for building and evaluating provenance-based intrusion detection systems (PIDSs), addressi...

[2601.05151] ROOFS: RObust biOmarker Feature Selection

The paper introduces ROOFS, a Python package for robust biomarker feature selection, addressing challenges in biomedical data through com...

[2511.08851] Learning-based Radio Link Failure Prediction Based on Measurement Dataset in Railway Environments

This article discusses a study on predicting radio link failures in railway environments using machine learning models, focusing on early...

[2509.16606] Bayesian Ego-graph Inference for Networked Multi-Agent Reinforcement Learning

The paper presents BayesG, a decentralized actor-framework for networked multi-agent reinforcement learning (MARL) that enhances adaptabi...

[2508.21418] From slides to AI-ready maps: Standardized multi-layer tissue maps as metadata for artificial intelligence in digital pathology

This article presents a framework for creating standardized multi-layer tissue maps as metadata for AI in digital pathology, enhancing th...

[2507.21372] Load Balancing for AI Training Workloads

This paper evaluates various load-balancing designs for AI training workloads, revealing that packet spraying outperforms traditional met...

[2502.15110] Variational phylogenetic inference with products over bipartitions

This paper presents a novel variational Bayesian method for inferring ultrametric phylogenetic trees, improving accuracy and efficiency i...

[2505.04586] Active Sampling for MRI-based Sequential Decision Making

This article presents a novel multi-objective reinforcement learning framework for MRI-based sequential decision-making, improving diagno...

[2410.03041] Minmax Trend Filtering: Generalizations of Total Variation Denoising via a Local Minmax/Maxmin Formula

The paper introduces Minmax Trend Filtering (MTF), a novel approach to Total Variation Denoising (TVD) that utilizes a local minmax/maxmi...