Data analysis, statistics, and data engineering
UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...
Google's new offline-first dictation app uses Gemma AI models to take on the apps like Wispr Flow.
This article reviews the top 10 AI certifications and courses for 2026, highlighting their significance in a rapidly evolving field and t...
![[2602.17554] A Theoretical Framework for Modular Learning of Robust Generative Models](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
This article presents a theoretical framework for modular learning in robust generative models, exploring the combination of domain-speci...
The paper presents a novel algorithm for generating provably minimal explanations for Neural Additive Models (NAMs), improving efficiency...
The paper introduces a novel approach to variational inference (VI) by optimizing radial profiles, enhancing the approximation of high-di...
This paper explores the application of machine learning to classify geometric knots, addressing the challenge of identifying equivalent e...
This article presents a machine learning framework that analyzes carotid ultrasound videos to identify vascular damage, enhancing early d...
This paper presents a generative modeling framework using Wasserstein Autoencoders to optimize laser pulse shaping in photoinjector syste...
The paper presents SCOPE, a novel framework for fine-tuning EEG foundation models, addressing challenges in generalization under limited ...
CounterFlowNet introduces a novel generative approach for creating counterfactual explanations in machine learning, enhancing interpretab...
The paper introduces ZO-Muon, a novel zeroth-order optimization method that enhances convergence speed and accuracy in training large-sca...
This paper explores online learning models using improving agents, focusing on multiclass setups, budgeted agents, and bandit learners, e...
This paper introduces a locality radius framework to understand relational inductive bias in database learning, focusing on the necessary...
This paper presents a serverless MLOps framework for the complete ML lifecycle, focusing on Harmonized System code prediction, achieving ...
This article presents a novel approach to stochastic closure modeling by integrating transport-based generative models with latent geomet...
The paper presents MeGU, a novel framework for machine unlearning that addresses the challenge of effectively erasing target data while p...
This article presents NAMO and NAMO-D, new optimizers that enhance adaptive moment estimation by integrating orthogonalized momentum, sho...
This paper introduces STDSH-MARL, a novel framework for human-centric traffic signal control that enhances multimodal transportation effi...
The paper presents the Multi-Probe Zero Collision Hash (MPZCH), a novel indexing method that mitigates embedding collisions in large-scal...
The paper introduces WS-GRPO, a method for improving rollout efficiency in language model training by providing correctness-aware guidanc...
This paper presents a framework for certifying data-poisoning attacks in neural networks using mixed-integer programming, ensuring robust...
This study presents a classification model for predicting dementia in Brazilian adults aged 50 and over, utilizing data from the Brazilia...
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