Limitations of nonlinear PCA as performed with generic neural networks. - Edward C. Malthouse (IEEE Trans. Neural Networks, 1998)

Mining for trigger events with survival analysis. - Edward C. Malthouse (Data Min. Knowl. Discov., 2007)

Quantifying the indirect effects of a marketing contact. - Dingxi Qiu; Edward C. Malthouse (Expert Syst. Appl., 2009)

Cluster Analysis with General Latent Class Model. - Dingxi Qiu; Edward C. Malthouse (Encyclopedia of Data Warehousing and Mining, 2009)

Accounting for the long-term effects of a marketing contact. - Edward C. Malthouse (Expert Syst. Appl., 2010)

Optimal selection of media vehicles using customer databases. - Edward C. Malthouse; Dingxi Qiu; Jie Xu 004 (Expert Syst. Appl., 2012)

Media consumption across platforms: Identifying user-defined repertoires. - Harsh Taneja; James G. Webster; Edward C. Malthouse; Thomas Ksiazek (New Media Soc., 2012)

The Value of Online Customer Reviews. - Georgios Askalidis; Edward C. Malthouse (RecSys, 2016)

"Understanding a fury in your words": The effects of posting and viewing electronic negative word-of-mouth on purchase behaviors. - Su Jung Kim; Rebecca Jen-Hui Wang; Ewa Maslowska; Edward C. Malthouse (Comput. Hum. Behav., 2016)

Understanding and Overcoming Biases in Customer Reviews. - Georgios Askalidis; Edward C. Malthouse (CoRR, 2016)

Understanding and overcoming biases in online review systems. - Georgios Askalidis; Su Jung Kim; Edward C. Malthouse (Decis. Support Syst., 2017)

Do customer reviews drive purchase decisions? The moderating roles of review exposure and price. - Ewa Maslowska; Edward C. Malthouse; Vijay Viswanathan 003 (Decis. Support Syst., 2017)

Multistakeholder recommendation with provider constraints. - Özge Sürer; Robin Burke; Edward C. Malthouse (RecSys, 2018)

Recommendation in multistakeholder environments. - Robin Burke; Himan Abdollahpouri; Edward C. Malthouse; K. P. Thai; Yongfeng Zhang (RecSys, 2019)

RMSE: Workshop on Recommendation in Multi-stakeholder Environments. - Robin Burke; Himan Abdollahpouri; Edward C. Malthouse; K. P. Thai; Yongfeng Zhang (RMSE@RecSys, 2019)

A Multistakeholder Recommender Systems Algorithm for Allocating Sponsored Recommendations. - Edward C. Malthouse; Khadija Ali Vakeel; Yasaman Kamyab Hessary; Robin Burke; Morana Fuduric (RMSE@RecSys, 2019)

Towards an Experimental News User Community as Infrastructure for Recommendation Research (abstract). - Joseph A. Konstan; Robin Burke; Edward C. Malthouse (INRA@RecSys, 2021)

Toward the Next Generation of News Recommender Systems (Abstract). - Edward C. Malthouse (KaRS/ComplexRec@RecSys, 2021)

A Constrained Optimization Approach for Calibrated Recommendations. - Sinan Seymen; Himan Abdollahpouri; Edward C. Malthouse (RecSys, 2021)

A Unified Optimization Toolbox for Solving Popularity Bias, Fairness, and Diversity in Recommender Systems. - Sinan Seymen; Himan Abdollahpouri; Edward C. Malthouse (MORS@RecSys, 2021)

User-centered Evaluation of Popularity Bias in Recommender Systems. - Himan Abdollahpouri; Masoud Mansoury; Robin Burke; Bamshad Mobasher; Edward C. Malthouse (UMAP, 2021)

Toward the Next Generation of News Recommender Systems. - Himan Abdollahpouri; Edward C. Malthouse; Joseph A. Konstan; Bamshad Mobasher; Jeremy Gilbert (WWW (Companion Volume), 2021)

Coefficient tree regression for generalized linear models. - Özge Sürer; Daniel W. Apley; Edward C. Malthouse (Stat. Anal. Data Min., 2021)

An Interpretable Neural Network Model for Bundle Recommendations: Doctoral Symposium, Extended Abstract. - Xinyi Li; Edward C. Malthouse (RecSys, 2022)

Making Smart Recommendations for Perishable and Stockout Products. - Sinan Seymen; Anna-Lena Sachs; Edward C. Malthouse (MORS@RecSys, 2022)

A Benchmark for Text Classification in News Recommendations. - Xinyi Li; Edward C. Malthouse (INRA/IWILDS@SIGIR, 2022)

The 10th International Workshop on News Recommendation and Analytics (INRA 2022). - Özlem Özgöbek; Andreas Lommatzsch; Benjamin Kille; Peng Liu 025; Jon Atle Gulla; Edward C. Malthouse (SIGIR, 2022)

A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, and Fake News. - Xinyi Li; Yongfeng Zhang; Edward C. Malthouse (INRA@RecSys, 2023)

PBNR: Prompt-based News Recommender System. - Xinyi Li; Yongfeng Zhang; Edward C. Malthouse (CoRR, 2023)

A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake News. - Xinyi Li; Yongfeng Zhang; Edward C. Malthouse (CoRR, 2023)

Exploring Fine-tuning ChatGPT for News Recommendation. - Xinyi Li; Yongfeng Zhang; Edward C. Malthouse (CoRR, 2023)

Large Language Model Agentic Approach to Fact Checking and Fake News Detection. - Xinyi Li; Yongfeng Zhang; Edward C. Malthouse (ECAI, 2024)

Prompt-Based Generative News Recommendation (PGNR): Accuracy and Controllability. - Xinyi Li; Yongfeng Zhang; Edward C. Malthouse (ECIR (2), 2024)

Conducting User Experiments in Recommender Systems. - Bart P. Knijnenburg; Edward C. Malthouse (RecSys, 2024)

Fifth Generation IMC: Expanding the scope to Profit, People, and the Planet. - Stewart Pearson; Edward C. Malthouse (CoRR, 2024)

Large Language Model Agent for Fake News Detection. - Xinyi Li; Yongfeng Zhang; Edward C. Malthouse (CoRR, 2024)

Large Language Model-driven Multi-Agent Simulation for News Diffusion Under Different Network Structures. - Xinyi Li; Yu Xu; Yongfeng Zhang; Edward C. Malthouse (CoRR, 2024)

Coefficient tree regression: fast, accurate and interpretable predictive modeling. - Özge Sürer; Daniel W. Apley; Edward C. Malthouse (Mach. Learn., 2024)

Discovering interpretable structure in longitudinal predictors via coefficient trees. - Özge Sürer; Daniel W. Apley; Edward C. Malthouse (Adv. Data Anal. Classif., 2024)

Optimising customer equity through engagement. - Yayu Zhou; Edward C. Malthouse; Barry L. Nelson (J. Oper. Res. Soc., 2025)