Imagen de Portada

Competition-Aware CPC Forecasting with Near-Market Coverage

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Frey, Sebastian, Beccari, Edoardo, Kranz, Maximilian, Pellizzari, Nicolò Alberto, Karaman, Ali Mete, Han, Qiwei, Kaiser, Maximilian
Formato:	Preprint
Publicado:	2026
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

Interpretable Deep Learning for Forecasting Online Advertising Costs: Insights from the Competitive Bidding Landscape
por: Oldenburg, Fynn, et al.
Publicado: (2023)

Cross-Platform E-Commerce Product Categorization and Recategorization: A Multimodal Hierarchical Classification Approach
por: Gross, Lotte, et al.
Publicado: (2025)

Variance-Aware Prior-Based Tree Policies for Monte Carlo Tree Search
por: Weichart, Maximilian
Publicado: (2025)

Representation Homogeneity and Systemic Instability in AI-Dominated Financial Markets: A Structural Approach
por: Qiu, Yimeng, et al.
Publicado: (2026)

From High-Dimensional Spaces to Verifiable ODD Coverage for Safety-Critical AI-based Systems
por: Stefani, Thomas, et al.
Publicado: (2026)

Relative Geometry of Neural Forecasters: Linking Accuracy and Alignment in Learned Latent Geometry
por: Kucukahmetler, Deniz, et al.
Publicado: (2026)

FlashRNN: I/O-Aware Optimization of Traditional RNNs on modern hardware
por: Pöppel, Korbinian, et al.
Publicado: (2024)

ConTextTab: A Semantics-Aware Tabular In-Context Learner
por: Spinaci, Marco, et al.
Publicado: (2025)

A Theory of Interpretable Approximations
por: Bressan, Marco, et al.
Publicado: (2024)

Discovering Behavioral Predispositions in Data to Improve Human Activity Recognition
por: Popko, Maximilian, et al.
Publicado: (2022)

Joint Localization and Planning using Diffusion
por: Beyer, L. Lao, et al.
Publicado: (2024)

Near-Optimal Regret for KL-Regularized Multi-Armed Bandits
por: Ji, Kaixuan, et al.
Publicado: (2026)

Online Curvature-Aware Replay: Leveraging $\mathbf{2^{nd}}$ Order Information for Online Continual Learning
por: Urettini, Edoardo, et al.
Publicado: (2025)

Simple Baselines are Competitive with Code Evolution
por: Gideoni, Yonatan, et al.
Publicado: (2026)

A Deep Learning Framework for Heat Demand Forecasting using Time-Frequency Representations of Decomposed Features
por: Ramachandran, Adithya, et al.
Publicado: (2026)

ECQ$^{\text{x}}$: Explainability-Driven Quantization for Low-Bit and Sparse DNNs
por: Becking, Daniel, et al.
Publicado: (2021)

Diversity-Aware Adaptive Collocation for Physics-Informed Neural Networks via Sparse QUBO Optimization and Hybrid Coresets
por: Salloum, Hadi, et al.
Publicado: (2026)

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

From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation
por: Achtibat, Reduan, et al.
Publicado: (2022)

DSL: Understanding and Improving Softmax Recommender Systems with Competition-Aware Scaling
por: Sahyouni, Bucher, et al.
Publicado: (2026)

Error Broadcast and Decorrelation as a Potential Artificial and Natural Learning Mechanism
por: Erdogan, Mete, et al.
Publicado: (2025)

Efficient Large Language Model Inference with Neural Block Linearization
por: Erdogan, Mete, et al.
Publicado: (2025)

Live or Lie: Action-Aware Capsule Multiple Instance Learning for Risk Assessment in Live Streaming Platforms
por: Qiao, Yiran, et al.
Publicado: (2026)

Reasoning-Aware Training for Time Series Forecasting
por: Ahamed, Md Atik, et al.
Publicado: (2026)

HOP to the Next Tasks and Domains for Continual Learning in NLP
por: Michieli, Umberto, et al.
Publicado: (2024)

From What to How: Attributing CLIP's Latent Components Reveals Unexpected Semantic Reliance
por: Dreyer, Maximilian, et al.
Publicado: (2025)

MMCTOP: A Multimodal Textualization and Mixture-of-Experts Framework for Clinical Trial Outcome Prediction
por: Aparício, Carolina, et al.
Publicado: (2025)

Solving Robust Markov Decision Processes: Generic, Reliable, Efficient
por: Meggendorfer, Tobias, et al.
Publicado: (2024)

LLMs for Text-Based Exploration and Navigation Under Partial Observability
por: Sandfuchs, Stephan, et al.
Publicado: (2026)

Physics-Inspired Interpretability Of Machine Learning Models
por: Niroomand, Maximilian P, et al.
Publicado: (2023)

Neural Cluster First, Route Second: One-Shot Capacitated Vehicle Routing via Differentiable Optimal Transport
por: Chin, Samuel J. K., et al.
Publicado: (2026)

DDTR: Diffusion Denoising Trace Recovery
por: Matyash, Maximilian, et al.
Publicado: (2025)

Target-Aligned Reinforcement Learning
por: Pleiss, Leonard S., et al.
Publicado: (2026)

Weather Prediction with Diffusion Guided by Realistic Forecast Processes
por: Hua, Zhanxiang, et al.
Publicado: (2024)

Accelerating HEC-RAS: A Recurrent Neural Operator for Rapid River Forecasting
por: Holmberg, Edward, et al.
Publicado: (2025)

KVzap: Fast, Adaptive, and Faithful KV Cache Pruning
por: Jegou, Simon, et al.
Publicado: (2026)

FloydNet: A Learning Paradigm for Global Relational Reasoning
por: Yu, Jingcheng, et al.
Publicado: (2026)

Pairwise Difference Learning for Classification
por: Belaid, Mohamed Karim, et al.
Publicado: (2024)

Weighted Contrastive Learning for Anomaly-Aware Time-Series Forecasting
por: Ekstrand, Joel, et al.
Publicado: (2025)

Conformal Prediction for Electricity Price Forecasting in the Day-Ahead and Real-Time Balancing Market
por: O'Connor, Ciaran, et al.
Publicado: (2025)