Saved in:
| Main Author: | Ardeshirifar, Ramtin |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.01244 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Non-Contact Breath Rate Classification Using SVM Model and mmWave Radar Sensor Data
by: Ali, Mohammad Wassaf, et al.
Published: (2024)
by: Ali, Mohammad Wassaf, et al.
Published: (2024)
Less Discriminatory Alternative and Interpretable XGBoost Framework for Binary Classification
by: Pangia, Andrew, et al.
Published: (2024)
by: Pangia, Andrew, et al.
Published: (2024)
Real-Time Weather Image Classification with SVM
by: Ship, Eden, et al.
Published: (2024)
by: Ship, Eden, et al.
Published: (2024)
Comparative Analysis of FOLD-SE vs. FOLD-R++ in Binary Classification and XGBoost in Multi-Category Classification
by: Murthy, Akshay, et al.
Published: (2025)
by: Murthy, Akshay, et al.
Published: (2025)
Cryptocurrency Price Forecasting Using XGBoost Regressor and Technical Indicators
by: Hafid, Abdelatif, et al.
Published: (2024)
by: Hafid, Abdelatif, et al.
Published: (2024)
Decentralized Low-Rank Fine-Tuning of Large Language Models
by: Ghiasvand, Sajjad, et al.
Published: (2025)
by: Ghiasvand, Sajjad, et al.
Published: (2025)
Scaling Up Diffusion and Flow-based XGBoost Models
by: Cresswell, Jesse C., et al.
Published: (2024)
by: Cresswell, Jesse C., et al.
Published: (2024)
Composite Quantile Regression With XGBoost Using the Novel Arctan Pinball Loss
by: Sluijterman, Laurens, et al.
Published: (2024)
by: Sluijterman, Laurens, et al.
Published: (2024)
The Impact of Battery Cell Configuration on Electric Vehicle Performance: An XGBoost-Based Classification with SHAP Interpretability
by: Wishal, Santanam, et al.
Published: (2026)
by: Wishal, Santanam, et al.
Published: (2026)
Prediction Of Cryptocurrency Prices Using LSTM, SVM And Polynomial Regression
by: Giffary, Novan Fauzi Al, et al.
Published: (2024)
by: Giffary, Novan Fauzi Al, et al.
Published: (2024)
Uncertainty Quantification in SVM prediction
by: Anand, Pritam
Published: (2025)
by: Anand, Pritam
Published: (2025)
Inverse Reinforcement Learning by Estimating Expertise of Demonstrators
by: Beliaev, Mark, et al.
Published: (2024)
by: Beliaev, Mark, et al.
Published: (2024)
Multiview learning with twin parametric margin SVM
by: Quadir, A., et al.
Published: (2024)
by: Quadir, A., et al.
Published: (2024)
Concept Drift Visualization of SVM with Shifting Window
by: Galmeanu, Honorius, et al.
Published: (2024)
by: Galmeanu, Honorius, et al.
Published: (2024)
REALM: Reliable Expertise-Aware Language Model Fine-Tuning from Noisy Annotations
by: Ghiasvand, Sajjad, et al.
Published: (2026)
by: Ghiasvand, Sajjad, et al.
Published: (2026)
An Autotuning-based Optimization Framework for Mixed-kernel SVM Classifications in Smart Pixel Datasets and Heterojunction Transistors
by: Wu, Xingfu, et al.
Published: (2024)
by: Wu, Xingfu, et al.
Published: (2024)
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients
by: Wang, Mengdi, et al.
Published: (2024)
by: Wang, Mengdi, et al.
Published: (2024)
Unlocking Your Sales Insights: Advanced XGBoost Forecasting Models for Amazon Products
by: Wang, Meng, et al.
Published: (2024)
by: Wang, Meng, et al.
Published: (2024)
Detecting Distributed Denial of Service Attacks Using Logistic Regression and SVM Methods
by: Ullah, Mohammad Arafat, et al.
Published: (2024)
by: Ullah, Mohammad Arafat, et al.
Published: (2024)
Efficient Cybersecurity Assessment Using SVM and Fuzzy Evidential Reasoning for Resilient Infrastructure
by: Ali, Zaydon L., et al.
Published: (2025)
by: Ali, Zaydon L., et al.
Published: (2025)
Few-Shot Adversarial Low-Rank Fine-Tuning of Vision-Language Models
by: Ghiasvand, Sajjad, et al.
Published: (2025)
by: Ghiasvand, Sajjad, et al.
Published: (2025)
Smooth Ranking SVM via Cutting-Plane Method
by: Ozcan, Erhan Can, et al.
Published: (2024)
by: Ozcan, Erhan Can, et al.
Published: (2024)
On the Impact of Weight Discretization in QUBO-Based SVM Training
by: Mücke, Sascha
Published: (2025)
by: Mücke, Sascha
Published: (2025)
pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models
by: Ghiasvand, Sajjad, et al.
Published: (2025)
by: Ghiasvand, Sajjad, et al.
Published: (2025)
ZKBoost: Zero-Knowledge Verifiable Training for XGBoost
by: Melissaris, Nikolas, et al.
Published: (2026)
by: Melissaris, Nikolas, et al.
Published: (2026)
XGenBoost: Synthesizing Small and Large Tabular Datasets with XGBoost
by: Achterberg, Jim, et al.
Published: (2026)
by: Achterberg, Jim, et al.
Published: (2026)
Sidewalk Hazard Detection Using Variational Autoencoder and One-Class SVM
by: Guzman, Edgar, et al.
Published: (2024)
by: Guzman, Edgar, et al.
Published: (2024)
Probabilistic Quantum SVM Training on Ising Machine
by: He, Haoqi, et al.
Published: (2025)
by: He, Haoqi, et al.
Published: (2025)
Generalization Properties of Adversarial Training for $\ell_0$-Bounded Adversarial Attacks
by: Delgosha, Payam, et al.
Published: (2024)
by: Delgosha, Payam, et al.
Published: (2024)
LLMPi: Optimizing LLMs for High-Throughput on Raspberry Pi
by: Ardakani, Mahsa, et al.
Published: (2025)
by: Ardakani, Mahsa, et al.
Published: (2025)
What Functions Does XGBoost Learn?
by: Ki, Dohyeong, et al.
Published: (2026)
by: Ki, Dohyeong, et al.
Published: (2026)
Dynamic Meta-Learning for Adaptive XGBoost-Neural Ensembles
by: Sedek, Arthur
Published: (2025)
by: Sedek, Arthur
Published: (2025)
Estimation of Fish Catch Using Sentinel-2, 3 and XGBoost-Kernel-Based Kernel Ridge Regression
by: Mohammed, Kanu, et al.
Published: (2026)
by: Mohammed, Kanu, et al.
Published: (2026)
Datasheets for AI and medical datasets (DAIMS): a data validation and documentation framework before machine learning analysis in medical research
by: Marandi, Ramtin Zargari, et al.
Published: (2025)
by: Marandi, Ramtin Zargari, et al.
Published: (2025)
$p$SVM: Soft-margin SVMs with $p$-norm Hinge Loss
by: Sun, Haoxiang
Published: (2024)
by: Sun, Haoxiang
Published: (2024)
ODTE -- An ensemble of multi-class SVM-based oblique decision trees
by: Montañana, Ricardo, et al.
Published: (2024)
by: Montañana, Ricardo, et al.
Published: (2024)
An Efficient Variant of One-Class SVM with Lifelong Online Learning Guarantees
by: Suk, Joe, et al.
Published: (2025)
by: Suk, Joe, et al.
Published: (2025)
The effect of different feature selection methods on models created with XGBoost
by: Neyra, Jorge, et al.
Published: (2024)
by: Neyra, Jorge, et al.
Published: (2024)
DeepSVM: Learning Stochastic Volatility Models with Physics-Informed Deep Operator Networks
by: Malandain, Kieran A., et al.
Published: (2025)
by: Malandain, Kieran A., et al.
Published: (2025)
In-field Calibration of Low-Cost Sensors through XGBoost $\&$ Aggregate Sensor Data
by: Yin, Kevin, et al.
Published: (2025)
by: Yin, Kevin, et al.
Published: (2025)
Similar Items
-
Non-Contact Breath Rate Classification Using SVM Model and mmWave Radar Sensor Data
by: Ali, Mohammad Wassaf, et al.
Published: (2024) -
Less Discriminatory Alternative and Interpretable XGBoost Framework for Binary Classification
by: Pangia, Andrew, et al.
Published: (2024) -
Real-Time Weather Image Classification with SVM
by: Ship, Eden, et al.
Published: (2024) -
Comparative Analysis of FOLD-SE vs. FOLD-R++ in Binary Classification and XGBoost in Multi-Category Classification
by: Murthy, Akshay, et al.
Published: (2025) -
Cryptocurrency Price Forecasting Using XGBoost Regressor and Technical Indicators
by: Hafid, Abdelatif, et al.
Published: (2024)