:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Yin, Kevin, Gersey, Julia, Zhang, Pei
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2506.15840
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SenDaL: An Effective and Efficient Calibration Framework of Low-Cost Sensors for Daily Life
by: Ahn, Seokho, et al.
Published: (2025)

Privacy-Preserving Bathroom Monitoring for Elderly Emergencies Using PIR and LiDAR Sensors
by: Sidibé, Youssouf, et al.
Published: (2025)

Provably Outlier-resistant Semi-parametric Regression for Transferable Calibration of Low-cost Air-quality Sensors
by: Chaurasia, Divyansh, et al.
Published: (2025)

Time Aggregation Features for XGBoost Models
by: Pinchuk, Mykola
Published: (2026)

Real-time Calibration Model for Low-cost Sensor in Fine-grained Time series
by: Ahn, Seokho, et al.
Published: (2024)

Likelihood-based Sensor Calibration using Affine Transformation
by: Machhamer, Rüdiger, et al.
Published: (2023)

Statistical Study of Sensor Data and Investigation of ML-based Calibration Algorithms for Inexpensive Sensor Modules: Experiments from Cape Point
by: Barrett, Travis, et al.
Published: (2025)

Veli: Unsupervised Method and Unified Benchmark for Low-Cost Air Quality Sensor Correction
by: Dalbah, Yahia, et al.
Published: (2025)

PhishNet: A Phishing Website Detection Tool using XGBoost
by: Kumar, Prashant, et al.
Published: (2024)

Low-Cost Sensor Fusion Framework for Organic Substance Classification and Quality Control Using Classification Methods
by: Chowdhury, Borhan Uddin, et al.
Published: (2025)

Sensor Calibration Model Balancing Accuracy, Real-time, and Efficiency
by: Yun, Jinyong, et al.
Published: (2025)

Assessing Low Back Movement with Motion Tape Sensor Data Through Deep Learning
by: Levy, Jared, et al.
Published: (2026)

Preliminary Characterization of Bio-inspired Dog-Nose Sampler for Aerosol Detection
by: Naveed, Yahya, et al.
Published: (2025)

ZV-Sim: Probabilistic Simulation Framework for Pre-emergent Novel Zoonose Tracking
by: Maffetone, Joseph, et al.
Published: (2025)

M$^2$AD: Multi-Sensor Multi-System Anomaly Detection through Global Scoring and Calibrated Thresholding
by: Alnegheimish, Sarah, et al.
Published: (2025)

Olfactory Inertial Odometry: Sensor Calibration and Drift Compensation
by: France, Kordel K., et al.
Published: (2025)

Federated Weather Modeling on Sensor Data
by: Chen, Shengchao, et al.
Published: (2026)

Less Discriminatory Alternative and Interpretable XGBoost Framework for Binary Classification
by: Pangia, Andrew, et al.
Published: (2024)

Histogram-Based Federated XGBoost using Minimal Variance Sampling for Federated Tabular Data
by: Lindskog, William, et al.
Published: (2024)

When Sensors Fail: Temporal Sequence Models for Robust PPO under Sensor Drift
by: Vogt-Lowell, Kevin, et al.
Published: (2026)

Q-SCALE: Quantum computing-based Sensor Calibration for Advanced Learning and Efficiency
by: Bergadano, Lorenzo, et al.
Published: (2024)

IGADA-IoT: IoT Sensor Energy Optimization in Wireless Sensor Networks Driven by Automatic Data Augmentation
by: Sun, Mingchun, et al.
Published: (2026)

Aligning Evaluation with Clinical Priorities: Calibration, Label Shift, and Error Costs
by: Flores, Gerardo A., et al.
Published: (2025)

Scaling Up Diffusion and Flow-based XGBoost Models
by: Cresswell, Jesse C., et al.
Published: (2024)

Adaptive State-Space Mamba for Real-Time Sensor Data Anomaly Detection
by: Zhang, Alice, et al.
Published: (2025)

On-Device Soft Sensors: Real-Time Fluid Flow Estimation from Level Sensor Data
by: Ling, Tianheng, et al.
Published: (2023)

LSM-2: Learning from Incomplete Wearable Sensor Data
by: Xu, Maxwell A., et al.
Published: (2025)

ZKBoost: Zero-Knowledge Verifiable Training for XGBoost
by: Melissaris, Nikolas, et al.
Published: (2026)

Cryptocurrency Price Forecasting Using XGBoost Regressor and Technical Indicators
by: Hafid, Abdelatif, et al.
Published: (2024)

XGenBoost: Synthesizing Small and Large Tabular Datasets with XGBoost
by: Achterberg, Jim, et al.
Published: (2026)

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling
by: Wei, Junhao, et al.
Published: (2026)

Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection
by: Kabane, Siyaxolisa
Published: (2024)

What Functions Does XGBoost Learn?
by: Ki, Dohyeong, et al.
Published: (2026)

SensorLM: Learning the Language of Wearable Sensors
by: Zhang, Yuwei, et al.
Published: (2025)

Dynamic Meta-Learning for Adaptive XGBoost-Neural Ensembles
by: Sedek, Arthur
Published: (2025)

Agile Climate-Sensor Design and Calibration Algorithms Using Machine Learning: Experiments From Cape Point
by: Barrett, Travis, et al.
Published: (2025)

Composite Quantile Regression With XGBoost Using the Novel Arctan Pinball Loss
by: Sluijterman, Laurens, et al.
Published: (2024)

Automated Classification of Dry Bean Varieties Using XGBoost and SVM Models
by: Ardeshirifar, Ramtin
Published: (2024)

Improving Realized LGD Approximation: A Novel Framework with XGBoost for Handling Missing Cash-Flow Data
by: Kostecka, Zuzanna, et al.
Published: (2024)

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation
by: Ma, Xing
Published: (2025)