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...

[2602.13098] Barron-Wiener-Laguerre models

The paper presents a probabilistic extension of Wiener-Laguerre models for causal operator learning, integrating Bayesian inference for e...

[2602.12972] Jointly Optimizing Debiased CTR and Uplift for Coupons Marketing: A Unified Causal Framework

This paper presents a novel framework, UniMVT, for optimizing debiased Click-Through Rate (CTR) and uplift in coupon marketing, addressin...

[2602.12937] Curriculum Learning and Pseudo-Labeling Improve the Generalization of Multi-Label Arabic Dialect Identification Models

This article presents a novel approach to Arabic Dialect Identification by framing it as a multi-label classification task, utilizing cur...

[2602.12932] TFTF: Training-Free Targeted Flow for Conditional Sampling

The paper presents a novel training-free method for conditional sampling in flow matching models, addressing the limitations of importanc...

[2602.12904] Nonparametric Contextual Online Bilateral Trade

This paper explores nonparametric contextual online bilateral trade, presenting an algorithm that optimizes trade pricing based on contex...

[2602.12923] Annealing in variational inference mitigates mode collapse: A theoretical study on Gaussian mixtures

This article presents a theoretical analysis of how annealing strategies can mitigate mode collapse in variational inference, particularl...

[2602.12903] Contextual Online Bilateral Trade

This paper explores contextual online bilateral trade, focusing on how agents' valuations depend on context vectors. It presents algorith...

[2602.12901] Blessings of Multiple Good Arms in Multi-Objective Linear Bandits

This paper explores the multi-objective linear bandit problem, revealing that multiple good arms can lead to implicit exploration, enhanc...

[2602.12866] Model-Aware Rate-Distortion Limits for Task-Oriented Source Coding

This paper explores Model-Aware Rate-Distortion Limits for Task-Oriented Source Coding, focusing on optimizing bitrate, latency, and task...

[2602.12778] Aspect-Based Sentiment Analysis for Future Tourism Experiences: A BERT-MoE Framework for Persian User Reviews

This article presents a novel BERT-MoE framework for aspect-based sentiment analysis (ABSA) tailored for Persian user reviews in the tour...

[2602.12696] Channel-Aware Probing for Multi-Channel Imaging

The paper presents Channel-Aware Probing (CAP), a method for improving multi-channel imaging (MCI) performance by leveraging inter-channe...

[2602.12680] A Regularization-Sharpness Tradeoff for Linear Interpolators

This paper introduces a regularization-sharpness tradeoff for linear interpolators in overparameterized settings, challenging traditional...

[2602.12681] Fool Me If You Can: On the Robustness of Binary Code Similarity Detection Models against Semantics-preserving Transformations

This paper evaluates the robustness of binary code similarity detection models against semantics-preserving transformations, introducing ...

[2602.12575] Discovering Semantic Latent Structures in Psychological Scales: A Response-Free Pathway to Efficient Simplification

This article presents a novel framework for simplifying psychological scales by discovering semantic latent structures without relying on...

[2602.12534] Linear Regression with Unknown Truncation Beyond Gaussian Features

This paper presents a novel algorithm for truncated linear regression when the survival set is unknown, improving efficiency and expandin...

[2602.12478] Task- and Metric-Specific Signal Quality Indices for Medical Time Series

The paper introduces a new perturbation-based signal quality index (pSQI) for medical time series, addressing the limitations of existing...

[2602.12426] Interference-Robust Non-Coherent Over-the-Air Computation for Decentralized Optimization

This paper presents an interference-robust non-coherent over-the-air computation (IR-NCOTA) method for decentralized optimization, enhanc...

[2602.12407] MiDAS: A Multimodal Data Acquisition System and Dataset for Robot-Assisted Minimally Invasive Surgery

The paper presents MiDAS, an open-source multimodal data acquisition system for robot-assisted minimally invasive surgery, enabling synch...

[2602.12349] Variational Green's Functions for Volumetric PDEs

This article presents a novel method called Variational Green's Function (VGF) for efficiently computing Green's functions for volumetric...

[2602.12301] Beyond Musical Descriptors: Extracting Preference-Bearing Intent in Music Queries

This article presents a novel dataset, MusicRecoIntent, aimed at understanding user intent in music queries by analyzing descriptors and ...