| 2025 | EMNLP | LLM-based Conversational Recommendation Agents with Collaborative Verbalized Experience. | Yaochen Zhu, Harald Steck, Dawen Liang, Yinhan He, Nathan Kallus, Jundong Li |
| 2025 | WWW | Does Weighting Improve Matrix Factorization for Recommender Systems? | Alex Ayoub, Samuel Robertson, Dawen Liang, Harald Steck, Nathan Kallus |
| 2025 | WWW | Collaborative Retrieval for Large Language Model-based Conversational Recommender Systems. | Yaochen Zhu, Chao Wan, Harald Steck, Dawen Liang, Yesu Feng, Nathan Kallus, Jundong Li |
| 2025 | WSDM | Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation. | Zhankui He, Zhouhang Xie, Harald Steck, Dawen Liang, Rahul Jha, Nathan Kallus, Julian J. McAuley |
| 2024 | RecSys | Neighborhood-Based Collaborative Filtering for Conversational Recommendation. | Zhouhang Xie, Junda Wu, Hyunsik Jeon, Zhankui He, Harald Steck, Rahul Jha, Dawen Liang, Nathan Kallus, Julian J. McAuley |
| 2024 | WWW | Is Cosine-Similarity of Embeddings Really About Similarity? | Harald Steck, Chaitanya Ekanadham, Nathan Kallus |
| 2023 | CIKM | Large Language Models as Zero-Shot Conversational Recommenders. | Zhankui He, Zhouhang Xie, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Prasad Majumder, Nathan Kallus, Julian J. McAuley |
| 2021 | RecSys | Negative Interactions for Improved Collaborative Filtering: Don't go Deeper, go Higher. | Harald Steck, Dawen Liang |
| 2020 | WSDM | ADMM SLIM: Sparse Recommendations for Many Users. | Harald Steck, Maria Dimakopoulou, Nickolai Riabov, Tony Jebara |
| 2019 | WWW | Embarrassingly Shallow Autoencoders for Sparse Data. | Harald Steck |
| 2018 | RecSys | Calibrated recommendations. | Harald Steck |
| 2015 | RecSys | Gaussian Ranking by Matrix Factorization. | Harald Steck |
| 2015 | RecSys | Interactive Recommender Systems: Tutorial. | Harald Steck, Roelof van Zwol, Chris Johnson |
| 2014 | RecSys | REDD 2014 - international workshop on recommender systems evaluation: dimensions and design. | Panagiotis Adamopoulos, Alejandro Bellogn, Pablo Castells, Paolo Cremonesi, Harald Steck |
| 2013 | RecSys | Evaluation of recommendations: rating-prediction and ranking. | Harald Steck |
| 2012 | KDD | Circle-based recommendation in online social networks. | Xiwang Yang, Harald Steck, Yong Liu |
| 2012 | RecSys | On top-k recommendation using social networks. | Xiwang Yang, Harald Steck, Yang Guo, Yong Liu |
| 2011 | IPIN | KL-divergence kernel regression for non-Gaussian fingerprint based localization. | Piotr Mirowski, Harald Steck, Philip Whiting, Ravishankar Palaniappan, Michael MacDonald, Tin Kam Ho |
| 2011 | RecSys | Item popularity and recommendation accuracy. | Harald Steck |
| 2011 | RecSys | Multi-value probabilistic matrix factorization for IP-TV recommendations. | Yu Xin, Harald Steck |
| 2010 | KDD | Training and testing of recommender systems on data missing not at random. | Harald Steck |
| 2010 | RecSys | A Generalized Probabilistic Framework and its Variants for Training Top-k Recommender System. | Harald Steck, Yu Xin |
| 2009 | AIME | Data-Efficient Information-Theoretic Test Selection. | Marianne Mueller, Rmer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, Stefan Kramer |
| 2009 | IDA | Subgroup Discovery for Test Selection: A Novel Approach and Its Application to Breast Cancer Diagnosis. | Marianne Mueller, Rmer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, Stefan Kramer |
| 2008 | UAI | Learning the Bayesian Network Structure: Dirichlet Prior vs Data. | Harald Steck |
| 2007 | IJCAI | Automated Heart Wall Motion Abnormality Detection from Ultrasound Images Using Bayesian Networks. | Maleeha Qazi, Glenn Fung, Sriram Krishnan, Rmer Rosales, Harald Steck, R. Bharat Rao, Don Poldermans, Dhanalakshmi Chandrasekaran |
| 2006 | UAI | Ranking by Dependence - A Fair Criteria. | Harald Steck |
| 2002 | UAI | Unsupervised Active Learning in Large Domains. | Harald Steck, Tommi S. Jaakkola |
| 2000 | UAI | On the Use of Skeletons when Learning in Bayesian Networks. | Harald Steck |