Harald Steck

ORCID

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 16

Top Venues

Technical University Munich, Germany (PHD)

Education History

Technical University Munich, Germany

PHD

Publications

Zhankui He, Zhouhang Xie, Harald Steck, Dawen Liang, Rahul Jha, Nathan Kallus, Julian J. McAuley
Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation. CoRR (2024)
Harald Steck, Chaitanya Ekanadham, Nathan Kallus
Is Cosine-Similarity of Embeddings Really About Similarity? WWW (Companion Volume) (2024)
Harald Steck, Chaitanya Ekanadham, Nathan Kallus
Is Cosine-Similarity of Embeddings Really About Similarity? CoRR (2024)
Zhankui He, Zhouhang Xie, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Prasad Majumder, Nathan Kallus, Julian J. McAuley
Large Language Models as Zero-Shot Conversational Recommenders. CoRR (2023)
Zhankui He, Zhouhang Xie, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Prasad Majumder, Nathan Kallus, Julian J. McAuley
Large Language Models as Zero-Shot Conversational Recommenders. CIKM (2023)
Harald Steck, Dawen Liang
Negative Interactions for Improved Collaborative Filtering: Don't go Deeper, go Higher. RecSys (2021)
Harald Steck, Dario García-García
On the Regularization of Autoencoders. CoRR (2021)
Harald Steck, Linas Baltrunas, Ehtsham Elahi, Dawen Liang, Yves Raimond, Justin Basilico
Deep Learning for Recommender Systems: A Netflix Case Study. AI Mag. 42 (3) (2021)
Harald Steck
Autoencoders that don't overfit towards the Identity. NeurIPS (2020)
Harald Steck, Maria Dimakopoulou, Nickolai Riabov, Tony Jebara
ADMM SLIM: Sparse Recommendations for Many Users. WSDM (2020)
Harald Steck
Embarrassingly Shallow Autoencoders for Sparse Data. CoRR (2019)
Harald Steck
Markov Random Fields for Collaborative Filtering. CoRR (2019)
Harald Steck
Collaborative Filtering via High-Dimensional Regression. CoRR (2019)
Harald Steck
Embarrassingly Shallow Autoencoders for Sparse Data. WWW (2019)
Harald Steck
Markov Random Fields for Collaborative Filtering. NeurIPS (2019)
Harald Steck
Calibrated recommendations. RecSys (2018)
Harald Steck, Roelof van Zwol, Chris Johnson
Interactive Recommender Systems: Tutorial. RecSys (2015)
Harald Steck
Gaussian Ranking by Matrix Factorization. RecSys (2015)
Panagiotis Adamopoulos, Alejandro Bellogín, Pablo Castells, Paolo Cremonesi, Harald Steck
REDD 2014 - international workshop on recommender systems evaluation: dimensions and design. RecSys (2014)
Xiwang Yang, Yang Guo, Yong Liu, Harald Steck
A survey of collaborative filtering based social recommender systems. Comput. Commun. 41 (2014)
Harald Steck
Evaluation of recommendations: rating-prediction and ranking. RecSys (2013)
Harald Steck
On the Use of Skeletons when Learning in Bayesian Networks CoRR (2013)
Harald Steck, Tommi S. Jaakkola
Unsupervised Active Learning in Large Domains CoRR (2013)
Harald Steck
Learning the Bayesian Network Structure: Dirichlet Prior versus Data CoRR (2012)
Piotr Mirowski, Philip Whiting, Harald Steck, Ravishankar Palaniappan, Michael MacDonald, Detlef Hartmann, Tin Kam Ho
Probability kernel regression for WiFi localisation. J. Locat. Based Serv. 6 (2) (2012)
Xiwang Yang, Harald Steck, Yong Liu
Circle-based recommendation in online social networks. KDD (2012)
Harald Steck
Ranking by Dependence - A Fair Criteria. CoRR (2012)
Xiwang Yang, Harald Steck, Yang Guo, Yong Liu
On top-k recommendation using social networks. RecSys (2012)
Tin Kam Ho, Kim Matthews, Lawrence O'Gorman, Harald Steck
Public Space Behavior Modeling With Video and Sensor Analytics. Bell Labs Tech. J. 16 (4) (2012)
Piotr Mirowski, Harald Steck, Philip Whiting, Ravishankar Palaniappan, Michael MacDonald, Tin Kam Ho
KL-divergence kernel regression for non-Gaussian fingerprint based localization. IPIN (2011)
Harald Steck
Item popularity and recommendation accuracy. RecSys (2011)
Yu Xin, Harald Steck
Multi-value probabilistic matrix factorization for IP-TV recommendations. RecSys (2011)
Harald Steck
Training and testing of recommender systems on data missing not at random. KDD (2010)
Harald Steck, Yu Xin
A Generalized Probabilistic Framework and its Variants for Training Top-k Recommender System. PRSAT@RecSys (2010)
Marianne Mueller, Rómer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, Stefan Kramer
Data-Efficient Information-Theoretic Test Selection. AIME (2009)
Marianne Mueller, Rómer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, Stefan Kramer
Subgroup Discovery for Test Selection: A Novel Approach and Its Application to Breast Cancer Diagnosis. IDA (2009)
Harald Steck
Learning the Bayesian Network Structure: Dirichlet Prior vs Data. UAI (2008)
Maleeha Qazi, Glenn Fung, Sriram Krishnan, Rómer Rosales, Harald Steck, R. Bharat Rao, Don Poldermans, Dhanalakshmi Chandrasekaran
Automated Heart Wall Motion Abnormality Detection from Ultrasound Images Using Bayesian Networks. IJCAI (2007)
Shipeng Yu, Balaji Krishnapuram, Rómer Rosales, Harald Steck, R. Bharat Rao
Bayesian Co-Training. NIPS (2007)
Harald Steck, Tommi S. Jaakkola
Predictive Discretization during Model Selection. AISTATS (2007)
Vikas C. Raykar, Harald Steck, Balaji Krishnapuram, Cary Dehing-Oberije, Philippe Lambin
On Ranking in Survival Analysis: Bounds on the Concordance Index. NIPS (2007)
Harald Steck
Hinge Rank Loss and the Area Under the ROC Curve. ECML (2007)
Harald Steck
Ranking by Dependence - A Fair Criteria. UAI (2006)
Harald Steck, Tommi S. Jaakkola
Predictive Discretization During Model Selection. DAGM-Symposium (2004)
Harald Steck, Tommi S. Jaakkola
Bias-Corrected Bootstrap and Model Uncertainty. NIPS (2003)
Harald Steck, Tommi S. Jaakkola
Unsupervised Active Learning in Large Domains. UAI (2002)
Harald Steck, Tommi S. Jaakkola
On the Dirichlet Prior and Bayesian Regularization. NIPS (2002)
Harald Steck
On the Use of Skeletons when Learning in Bayesian Networks. UAI (2000)

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Publication Activity (10 Years)

Top Topics

Top Venues

Harald Steck