Imagen de Portada

Iterative Causal Segmentation: Filling the Gap between Market Segmentation and Marketing Strategy

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ding, Kaihua, Cui, Jingsong, Soltani, Mohammad, Jin, Jing
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Variance-Bounded Evaluation of Entity-Centric AI Systems Without Ground Truth: Theory and Measurement
por: Ding, Kaihua
Publicado: (2025)

Market Making Strategies with Reinforcement Learning
por: Vicente, Óscar Fernández
Publicado: (2025)

An Exploration of Clustering Algorithms for Customer Segmentation in the UK Retail Market
por: John, Jeen Mary, et al.
Publicado: (2024)

Deep Causal Learning to Explain and Quantify The Geo-Tension's Impact on Natural Gas Market
por: Peter, Philipp Kai, et al.
Publicado: (2024)

Forecasting Foreign Exchange Market Prices Using Technical Indicators with Deep Learning and Attention Mechanism
por: Saadati, Sahabeh, et al.
Publicado: (2024)

Causal Unsupervised Semantic Segmentation
por: Kim, Junho, et al.
Publicado: (2023)

Invariant Causal Routing for Governing Social Norms in Online Market Economies
por: Yu, Xiangning, et al.
Publicado: (2026)

Objective Mispricing Detection for Shortlisting Undervalued Football Players via Market Dynamics and News Signals
por: Omejieke, Chinenye, et al.
Publicado: (2026)

A Causal Analysis of CO2 Reduction Strategies in Electricity Markets Through Machine Learning-Driven Metalearners
por: Naeini, Iman Emtiazi, et al.
Publicado: (2024)

Fill In The Gaps: Model Calibration and Generalization with Synthetic Data
por: Ba, Yang, et al.
Publicado: (2024)

MemPromptTSS: Persistent Prompt Memory for Iterative Multi-Granularity Time Series State Segmentation
por: Chang, Ching, et al.
Publicado: (2025)

Deep Learning-Based Forecasting of Hotel KPIs: A Cross-City Analysis of Global Urban Markets
por: Atapattu, C. J., et al.
Publicado: (2025)

Computational Arbitrage in AI Model Markets
por: Olmedo, Ricardo, et al.
Publicado: (2026)

From Patterns to Predictions: A Shapelet-Based Framework for Directional Forecasting in Noisy Financial Markets
por: Kim, Juwon, et al.
Publicado: (2025)

Iterative Mask Filling: An Effective Text Augmentation Method Using Masked Language Modeling
por: Kesgin, Himmet Toprak, et al.
Publicado: (2024)

Adaptive Segment-level Reward: Bridging the Gap Between Action and Reward Space in Alignment
por: Li, Yanshi, et al.
Publicado: (2024)

Competition-Aware CPC Forecasting with Near-Market Coverage
por: Frey, Sebastian, et al.
Publicado: (2026)

Caracal: Causal Architecture via Spectral Mixing
por: Gan, Bingzheng, et al.
Publicado: (2026)

Causally-Aware Information Bottleneck for Domain Adaptation
por: Javidian, Mohammad Ali
Publicado: (2026)

Stock Market Prediction Using Node Transformer Architecture Integrated with BERT Sentiment Analysis
por: Ridhawi, Mohammad Al, et al.
Publicado: (2026)

Mind the Gap: A Causal Perspective on Bias Amplification in Prediction & Decision-Making
por: Plecko, Drago, et al.
Publicado: (2024)

Learning to Price: Interpretable Attribute-Level Models for Dynamic Markets
por: Sethuraman, Srividhya, et al.
Publicado: (2026)

DecoKAN: Interpretable Decomposition for Forecasting Cryptocurrency Market Dynamics
por: Gao, Yuan, et al.
Publicado: (2025)

Transferring Information Across Interventions in Causal Bayesian Optimization
por: Javidian, Mohammad Ali
Publicado: (2026)

One Shot vs. Iterative: Rethinking Pruning Strategies for Model Compression
por: Janusz, Mikołaj, et al.
Publicado: (2025)

DeepArrhythmia: Segment-Contextualized ECG Arrhythmia Classification via Selective Evidence Acquisition
por: Li, Jiahui, et al.
Publicado: (2026)

An Expectation-Maximization Algorithm for Domain Adaptation in Gaussian Causal Models
por: Javidian, Mohammad Ali
Publicado: (2026)

Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
por: Binkyte, Ruta, et al.
Publicado: (2025)

Exploiting Temporal State Space Sharing for Video Semantic Segmentation
por: Hesham, Syed Ariff Syed, et al.
Publicado: (2025)

A Heterogeneous Graph-Based Multi-Task Learning for Fault Event Diagnosis in Smart Grid
por: Chanda, Dibaloke, et al.
Publicado: (2023)

Estimating Causal Effects from Learned Causal Networks
por: Raichev, Anna, et al.
Publicado: (2024)

Finding Optimal Trading History in Reinforcement Learning for Stock Market Trading
por: Montazeri, Sina, et al.
Publicado: (2025)

Iterative Amortized Inference: Unifying In-Context Learning and Learned Optimizers
por: Mittal, Sarthak, et al.
Publicado: (2025)

Localization Boosting for Growth Markets: Mitigating Cross-Locale Behavioral Bias in Learning-to-Rank
por: Seran, Suryaa Veerabathiran, et al.
Publicado: (2026)

AI in Manufacturing: Market Analysis and Opportunities
por: Abdelaal, Mohamed
Publicado: (2024)

Bayesian Regression for Predicting Subscription to Bank Term Deposits in Direct Marketing Campaigns
por: Tanvir, Muhammad Farhan, et al.
Publicado: (2024)

From Bias to Behavior: Learning Bull-Bear Market Dynamics with Contrastive Modeling
por: Luo, Xiaotong, et al.
Publicado: (2025)

Stock Market Price Prediction using Neural Prophet with Deep Neural Network
por: Chhibber, Navin, et al.
Publicado: (2026)

Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization
por: Gaur, Mudit, et al.
Publicado: (2024)

One-Step Abductive Multi-Target Learning with Diverse Noisy Samples and Its Application to Tumour Segmentation for Breast Cancer
por: Yang, Yongquan, et al.
Publicado: (2021)