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UMKC Announces New Master of Science in Artificial Intelligence
Ai Infrastructure

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...

AI News - General · 4 min ·
Google quietly launched an AI dictation app that works offline
Machine Learning

Google quietly launched an AI dictation app that works offline

Google's new offline-first dictation app uses Gemma AI models to take on the apps like Wispr Flow.

TechCrunch - AI · 4 min ·
Top 10 AI certifications and courses for 2026
Ai Startups

Top 10 AI certifications and courses for 2026

This article reviews the top 10 AI certifications and courses for 2026, highlighting their significance in a rapidly evolving field and t...

AI Events · 15 min ·

All Content

[2512.23405] On the Sample Complexity of Learning for Blind Inverse Problems
Machine Learning

[2512.23405] On the Sample Complexity of Learning for Blind Inverse Problems

This article explores the sample complexity of learning in blind inverse problems, providing theoretical insights and empirical validatio...

arXiv - Machine Learning · 4 min ·
[2510.14190] Contrastive Diffusion Alignment: Learning Structured Latents for Controllable Generation
Machine Learning

[2510.14190] Contrastive Diffusion Alignment: Learning Structured Latents for Controllable Generation

The paper presents Contrastive Diffusion Alignment (ConDA), a method that enhances the interpretability and control of diffusion models b...

arXiv - Machine Learning · 4 min ·
[2510.20220] Alternatives to the Laplacian for Scalable Spectral Clustering with Group Fairness Constraints
Ai Safety

[2510.20220] Alternatives to the Laplacian for Scalable Spectral Clustering with Group Fairness Constraints

This paper presents the Fair-SMW algorithm, an innovative approach to spectral clustering that enhances computational efficiency while en...

arXiv - Machine Learning · 4 min ·
[2510.13582] ArtNet: Hierarchical Clustering-Based Artificial Netlist Generator for ML and DTCO Application
Machine Learning

[2510.13582] ArtNet: Hierarchical Clustering-Based Artificial Netlist Generator for ML and DTCO Application

ArtNet introduces a novel artificial netlist generator that enhances machine learning model generalization and design-technology co-optim...

arXiv - Machine Learning · 4 min ·
[2509.22138] Slicing Wasserstein Over Wasserstein Via Functional Optimal Transport
Data Science

[2509.22138] Slicing Wasserstein Over Wasserstein Via Functional Optimal Transport

This article presents a novel approach to the Wasserstein over Wasserstein (WoW) distance by introducing the double-sliced Wasserstein (D...

arXiv - Machine Learning · 4 min ·
[2509.04583] Instance-Wise Adaptive Sampling for Dataset Construction in Approximating Inverse Problem Solutions
Machine Learning

[2509.04583] Instance-Wise Adaptive Sampling for Dataset Construction in Approximating Inverse Problem Solutions

This article presents a novel instance-wise adaptive sampling framework designed to enhance the efficiency of training datasets for super...

arXiv - Machine Learning · 4 min ·
[2505.17786] Supervised Graph Contrastive Learning for Gene Regulatory Networks
Machine Learning

[2505.17786] Supervised Graph Contrastive Learning for Gene Regulatory Networks

This article presents SupGCL, a novel supervised graph contrastive learning method for gene regulatory networks, leveraging biological pe...

arXiv - Machine Learning · 4 min ·
[2502.00204] Nearly-Optimal Bandit Learning in Stackelberg Games with Side Information
Machine Learning

[2502.00204] Nearly-Optimal Bandit Learning in Stackelberg Games with Side Information

This paper presents algorithms for nearly-optimal bandit learning in Stackelberg games, achieving improved regret rates and extending app...

arXiv - Machine Learning · 4 min ·
[2409.12709] SeqRisk: Transformer-augmented latent variable model for robust survival prediction with longitudinal data
Machine Learning

[2409.12709] SeqRisk: Transformer-augmented latent variable model for robust survival prediction with longitudinal data

SeqRisk introduces a transformer-augmented latent variable model for enhanced survival prediction using longitudinal healthcare data, add...

arXiv - Machine Learning · 3 min ·
[2410.23029] Risk-Aware Decision Making in Restless Bandits: Theory and Algorithms for Planning and Learning
Machine Learning

[2410.23029] Risk-Aware Decision Making in Restless Bandits: Theory and Algorithms for Planning and Learning

This paper explores risk-aware decision-making in restless bandits, proposing new algorithms for planning and learning that incorporate r...

arXiv - Machine Learning · 4 min ·
[2405.11454] Gradient Testing and Estimation by Comparisons
Machine Learning

[2405.11454] Gradient Testing and Estimation by Comparisons

The paper presents algorithms for gradient testing and estimation using a comparison oracle, optimizing query efficiency for smooth funct...

arXiv - Machine Learning · 3 min ·
[2403.11332] Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects
Machine Learning

[2403.11332] Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects

This paper presents a novel methodology combining graph machine learning and double machine learning to estimate causal effects in social...

arXiv - Machine Learning · 4 min ·
[2402.00851] Data Augmentation Scheme for Raman Spectra with Highly Correlated Annotations
Machine Learning

[2402.00851] Data Augmentation Scheme for Raman Spectra with Highly Correlated Annotations

This article presents a data augmentation scheme for Raman spectra, enhancing model training by generating additional data points with in...

arXiv - Machine Learning · 4 min ·
[2602.17654] Mine and Refine: Optimizing Graded Relevance in E-commerce Search Retrieval
Machine Learning

[2602.17654] Mine and Refine: Optimizing Graded Relevance in E-commerce Search Retrieval

The paper presents a two-stage framework called 'Mine and Refine' for optimizing graded relevance in e-commerce search retrieval, enhanci...

arXiv - Machine Learning · 4 min ·
[2602.17587] Asymptotically Optimal Sequential Testing with Markovian Data
Machine Learning

[2602.17587] Asymptotically Optimal Sequential Testing with Markovian Data

This paper presents a novel approach to sequential hypothesis testing for Markovian data, establishing new lower bounds and proposing an ...

arXiv - Machine Learning · 3 min ·
[2602.17577] Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction
Machine Learning

[2602.17577] Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction

This paper explores the concept of omniprediction in a multiclass setting, extending existing algorithms to address suboptimality bounds ...

arXiv - Machine Learning · 3 min ·
[2602.17565] Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning
Machine Learning

[2602.17565] Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning

This paper explores optimal unconstrained self-distillation in ridge regression, demonstrating strict improvements in prediction risk and...

arXiv - Machine Learning · 4 min ·
[2602.17543] genriesz: A Python Package for Automatic Debiased Machine Learning with Generalized Riesz Regression
Machine Learning

[2602.17543] genriesz: A Python Package for Automatic Debiased Machine Learning with Generalized Riesz Regression

The article presents 'genriesz', an open-source Python package designed for automatic debiased machine learning using generalized Riesz r...

arXiv - Machine Learning · 4 min ·
[2602.17314] Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE
Data Science

[2602.17314] Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE

This article surveys open datasets in learning analytics, identifying trends, challenges, and best practices to enhance research reproduc...

arXiv - Machine Learning · 4 min ·
[2602.17346] Partial Optimality in the Preordering Problem
Data Science

[2602.17346] Partial Optimality in the Preordering Problem

This paper explores the preordering problem, a complex issue in discrete mathematics, presenting new conditions and algorithms to enhance...

arXiv - Machine Learning · 3 min ·
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