Harald Steck

3.9k citations

39 papers · 2.1k indexed · 1 hit paper · h-index 20

Impact in

Information Systems top 0.5%
- Recommender Systems and Techniques
Management Science and Operations Research top 1%
- Advanced Bandit Algorithms Research

Papers in

Information Systems 19
- Recommender Systems and Techniques 19
Management Science and Operations Research 9
- Advanced Bandit Algorithms Research 9

Co-authors: Xiwang Yang Yong Liu Yang Guo Tommi Jaakkola Philippe Lambin Balaji Krishnapuram Cary Oberije Vikas C. Raykar
Journals: International Journal of Radiation Oncology*Biology*Physics (4 papers)Radiotherapy and Oncology (1 paper)British Journal of Cancer (1 paper)Computer Communications (1 paper)AI Magazine (1 paper)
Partner nations: United States Germany Netherlands

In The Last Decade

Harald Steck

35 papers receiving 2.0k citations

Hit Papers

align trajectories log scale

A survey of collaborative filtering based social recommender systems 2013 · 342 citations

Peers

Countries citing papers authored by Harald Steck

Since Specialization

Citations

This map shows the geographic impact of Harald Steck's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Harald Steck with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harald Steck more than expected).

Fields of papers citing papers by Harald Steck

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Harald Steck. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Harald Steck. The network helps show where Harald Steck may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Harald Steck, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Harald Steck Line = papers co-authored together Harald Steck links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Collaborative Retrieval for Large Language Model-based Conversational Recommender Systems Yaochen Zhu, М. И. Ершова, Harald Steck, Dawen Liang, Cynthia E. Myers, Nathan Kallus, Jundong Li	2025	2
2	Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation Zhankui He, Neiva Ketlyn Nunes dos Santos Leal, Harald Steck, Dawen Liang, Guili Lyu, Nathan Kallus, Julian McAuley	2025	0
3	Autoencoders that don't overfit towards the Identity Neural Information Processing Systems ·Harald Steck	2020	14
4	Calibrated recommendations Harald Steck	2018	139
5	Gaussian Ranking by Matrix Factorization Harald Steck	2015	14
6	Interactive Recommender Systems Harald Steck, Roelof van Zwol, Chris Johnson	2015	16
7	A survey of collaborative filtering based social recommender systems Computer Communications ·Xiwang Yang, Yang Guo, Yong Liu, Harald Steck Hit paper breakdown →	2013	342
8	KL-divergence kernel regression for non-Gaussian fingerprint based localization Piotr Mirowski, Harald Steck, Philip Whiting, Lauge Emil Nielsen, Michael B. MacDonald, Tin Kam Ho	2011	54
9	A Simple but Highly Effective Approach to Evaluate the Prognostic Performance of Gene Expression Signatures PLoS ONE ·Maud H. W. Starmans, Glenn Fung, Harald Steck, Bradly G. Wouters, Philippe Lambin	2011	13
10	A Generalized Probabilistic Framework and its Variants for Training Top-k Recommender System. Conference on Recommender Systems ·Harald Steck, Xin Yu	2010	5
11	Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types British Journal of Cancer ·Maud H. W. Starmans, Balaji Krishnapuram, Harald Steck, Hugo M. Horlings, Dimitry S.A. Nuyten, Marc J. van de Vijver, Renaud Seigneuric, Francesca M. Buffa, Adrian L. Harris, Bradly G. Wouters, Philippe Lambin	2008	36
12	Osteopontin Level to Creatinine Clearance Predicts Survival of NSCLC Patients International Journal of Radiation OncologyBiologyPhysics ·Harald Steck, C. Dehing, Hiska L. van der Weide, Dirk De Ruysscher, Leśnikowski Zj, S. Wanders, L. Boersma, Sheela Krishnan, F Batek, Philippe Lambin	2007	0
13	Automated heart wall motion abnormality detection from ultrasound images using Bayesian networks International Joint Conference on Artificial Intelligence ·Makoto Ishida, Glenn Fung, Sriram Krishnan, Rómer Rosales, Harald Steck, R. Bharat Rao, Don Poldermans, MarkPrein	2007	33
14	Tumor Volume Combined With Number of Positive Lymph Node Stations Is a More Important Prognostic Factor Than TNM Stage for Survival of Non–Small-Cell Lung Cancer Patients Treated With (Chemo)radiotherapy International Journal of Radiation OncologyBiologyPhysics ·Cary Oberije, Dirk De Ruysscher, Hiska L. van der Weide, Monique Hochstenbag, Gerben Bootsma, Wiel Geraedts, Cordula Pitz, Jean Simons, Jaap Teule, Ali Rahmy, Paul Thimister, Harald Steck, Philippe Lambin	2007	87
15	On Ranking in Survival Analysis: Bounds on the Concordance Index Harald Steck, Balaji Krishnapuram, Cary Oberije, Philippe Lambin, Vikas C. Raykar	2007	112
16	Models combining clinical data with medical knowledge are more accurate than doctors in predicting NSCLC after (chemo-)radiotherapy Radiotherapy and Oncology ·Harald Steck, C. Dehing, Hiska L. van der Weide, Dirk De Ruysscher, S. Nijsten, S. Wanders, L. Boersma, Ïâ ‰ Ëíó-Òúóï, S. Woutersen, Philippe Lambin	2006	0
17	2488 International Journal of Radiation OncologyBiologyPhysics ·C. Dehing, Hiska L. van der Weide, S. Wanders, L. Boersma, Dirk De Ruysscher, Leśnikowski Zj, Harald Steck, Ïâ ‰ Ëíó-Òúóï, Rohit Rao, Astri Ajeng Lestari	2006	1
18	Bias-Corrected Bootstrap and Model Uncertainty Harald Steck, Tommi Jaakkola	2003	22
19	Unsupervised active learning in large domains Uncertainty in Artificial Intelligence ·Harald Steck, Tommi Jaakkola	2002	9
20	On the Dirichlet Prior and Bayesian Regularization DSpace@MIT (Massachusetts Institute of Technology) ·Harald Steck, Tommi Jaakkola	2002	43

About Harald Steck

Harald Steck is a scholar working on Information Systems, Management Science and Operations Research, Artificial Intelligence, Signal Processing and Marketing, having authored 39 papers that have together received 2.1k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (19 papers), Advanced Bandit Algorithms Research (9 papers), Bayesian Modeling and Causal Inference (6 papers), Machine Learning and Algorithms (4 papers), Topic Modeling (4 papers), Indoor and Outdoor Localization Technologies (3 papers), Data Stream Mining Techniques (3 papers) and Machine Learning and Data Classification (3 papers). The work is most often cited by research in Information Systems (1.3k citations), Management Science and Operations Research (440 citations), Artificial Intelligence (871 citations), Computational Mathematics (13 citations) and Computer Vision and Pattern Recognition (347 citations). Harald Steck has collaborated with scholars based in United States, Germany and Netherlands. Frequent co-authors include Xiwang Yang, Yong Liu, Yang Guo, Yong Liu, Tommi Jaakkola, Philippe Lambin, Balaji Krishnapuram, Cary Oberije, Yang Guo and Vikas C. Raykar. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Radiotherapy and Oncology, British Journal of Cancer, Computer Communications and AI Magazine.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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