Copertina

Enhancing Predictive Accuracy in Pharmaceutical Sales Through An Ensemble Kernel Gaussian Process Regression Approach

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Mirshekari, Shahin, Moradi, Mohammadreza, Jafari, Hossein, Jafari, Mehdi, Ensaf, Mohammad
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Integrating Marketing Channels into Quantile Transformation and Bayesian Optimization of Ensemble Kernels for Sales Prediction with Gaussian Process Models
di: Mirshekari, Shahin, et al.
Pubblicazione: (2024)

Predicting Diabetes with Machine Learning Analysis of Income and Health Factors
di: Horestani, Fariba Jafari, et al.
Pubblicazione: (2024)

Universal Novelty Detection Through Adaptive Contrastive Learning
di: Mirzaei, Hossein, et al.
Pubblicazione: (2024)

GRAD: Real-Time Gated Recurrent Anomaly Detection in Autonomous Vehicle Sensors Using Reinforced EMA and Multi-Stage Sliding Window Techniques
di: Naeimi, Mohammad Hossein Jafari, et al.
Pubblicazione: (2025)

Generalization and Membership Inference Attack a Practical Perspective
di: Rahmani, Fateme, et al.
Pubblicazione: (2026)

The Power of Few: Accelerating and Enhancing Data Reweighting with Coreset Selection
di: Jafari, Mohammad, et al.
Pubblicazione: (2024)

Killing it with Zero-Shot: Adversarially Robust Novelty Detection
di: Mirzaei, Hossein, et al.
Pubblicazione: (2025)

Fractionally Supervised Classification with Maxima Nominated Samples
di: Jozani, Mohammad Jafari, et al.
Pubblicazione: (2026)

High-Dimensional Gaussian Process Regression with Soft Kernel Interpolation
di: Camaño, Chris, et al.
Pubblicazione: (2024)

Adaptive-lambda Subtracted Importance Sampled Scores in Machine Unlearning for DDPMs and VAEs
di: Dini, MohammadParsa, et al.
Pubblicazione: (2025)

Elite-Driven Support Vector Machines for Classification
di: Jozani, Mohammad Jafari, et al.
Pubblicazione: (2026)

Improving Trip Mode Choice Modeling Using Ensemble Synthesizer (ENSY)
di: Parsi, Amirhossein, et al.
Pubblicazione: (2024)

How Much Temporal Modeling is Enough? A Systematic Study of Hybrid CNN-RNN Architectures for Multi-Label ECG Classification
di: Jafari, Alireza, et al.
Pubblicazione: (2026)

Kernel Multigrid: Accelerate Back-fitting via Sparse Gaussian Process Regression
di: Zou, Lu, et al.
Pubblicazione: (2024)

Balcony: A Lightweight Approach to Dynamic Inference of Generative Language Models
di: Jamialahmadi, Benyamin, et al.
Pubblicazione: (2025)

DAK-UCB: Diversity-Aware Prompt Routing for LLMs and Generative Models
di: Jafari, Donya, et al.
Pubblicazione: (2026)

Reconstructing Blood Flow in Data-Poor Regimes: A Vasculature Network Kernel for Gaussian Process Regression
di: Ashtiani, Shaghayegh Z., et al.
Pubblicazione: (2024)

GP+: A Python Library for Kernel-based learning via Gaussian Processes
di: Yousefpour, Amin, et al.
Pubblicazione: (2023)

NeuroVascU-Net: A Unified Multi-Scale and Cross-Domain Adaptive Feature Fusion U-Net for Precise 3D Segmentation of Brain Vessels in Contrast-Enhanced T1 MRI
di: Vayeghan, Mohammad Jafari, et al.
Pubblicazione: (2025)

ArterialNet: Reconstructing Arterial Blood Pressure Waveform with Wearable Pulsatile Signals, a Cohort-Aware Approach
di: Huang, Sicong, et al.
Pubblicazione: (2024)

Empirical Asset Pricing via Ensemble Gaussian Process Regression
di: Filipović, Damir, et al.
Pubblicazione: (2022)

Guaranteed Coverage Prediction Intervals with Gaussian Process Regression
di: Papadopoulos, Harris
Pubblicazione: (2023)

Robust Semi-supervised Learning via $f$-Divergence and $α$-Rényi Divergence
di: Aminian, Gholamali, et al.
Pubblicazione: (2024)

Driving Safety Prediction and Safe Route Mapping Using In-vehicle and Roadside Data
di: Huang, Yufei, et al.
Pubblicazione: (2022)

Adversarial Robustness of Nonparametric Regression
di: Moradi, Parsa, et al.
Pubblicazione: (2025)

Survival Analysis of Young Triple-Negative Breast Cancer Patients
di: O, M. Mehdi Owrang, et al.
Pubblicazione: (2024)

NeRCC: Nested-Regression Coded Computing for Resilient Distributed Prediction Serving Systems
di: Moradi, Parsa, et al.
Pubblicazione: (2024)

Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
di: Cheng, Tin Sum, et al.
Pubblicazione: (2024)

Transformer Neural Processes - Kernel Regression
di: Jenson, Daniel, et al.
Pubblicazione: (2024)

Accuracy Improvement in Differentially Private Logistic Regression: A Pre-training Approach
di: Hoseinpour, Mohammad, et al.
Pubblicazione: (2023)

The Kernel Manifold: A Geometric Approach to Gaussian Process Model Selection
di: Islam, Md Shafiqul, et al.
Pubblicazione: (2026)

Networked Information Aggregation for Binary Classification
di: Bateni, MohammadHossein, et al.
Pubblicazione: (2026)

Electricity Price Prediction Using Multi-Kernel Gaussian Process Regression Combined with Kernel-Based Support Vector Regression
di: Das, Abhinav, et al.
Pubblicazione: (2024)

Wiring the 'Why': A Unified Taxonomy and Survey of Abductive Reasoning in LLMs
di: Salimi, Moein, et al.
Pubblicazione: (2026)

DeepBoost-AF: A Novel Unsupervised Feature Learning and Gradient Boosting Fusion for Robust Atrial Fibrillation Detection in Raw ECG Signals
di: Jafari, Alireza, et al.
Pubblicazione: (2025)

SalesRLAgent: A Reinforcement Learning Approach for Real-Time Sales Conversion Prediction and Optimization
di: M, Nandakishor
Pubblicazione: (2025)

Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach
di: Wang, Yinsong, et al.
Pubblicazione: (2024)

Spectral Anatomy of Quantum Gaussian Process Kernels
di: Xu, Jian, et al.
Pubblicazione: (2026)

Scalable Deep Basis Kernel Gaussian Processes
di: Zhu, Yunqin, et al.
Pubblicazione: (2025)

Likelihood-Free Gaussian Process for Regression
di: Shikuri, Yuta
Pubblicazione: (2020)