Harald Steck

According to our database, Harald Steck authored at least 42 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

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

CoRR, 2024

Is Cosine-Similarity of Embeddings Really About Similarity?

Harald Steck, Chaitanya Ekanadham, Nathan Kallus

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

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

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

2023

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

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2021

On the Regularization of Autoencoders.

Harald Steck, Dario García-García

CoRR, 2021

Deep Learning for Recommender Systems: A Netflix Case Study.

Harald Steck, Linas Baltrunas, Ehtsham Elahi, Dawen Liang, Yves Raimond, Justin Basilico

AI Mag., 2021

Negative Interactions for Improved Collaborative Filtering: Don't go Deeper, go Higher.

Harald Steck, Dawen Liang

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

2020

ADMM SLIM: Sparse Recommendations for Many Users.

Harald Steck, Maria Dimakopoulou, Nickolai Riabov, Tony Jebara

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Autoencoders that don't overfit towards the Identity.

Harald Steck

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Collaborative Filtering via High-Dimensional Regression.

Harald Steck

CoRR, 2019

Embarrassingly Shallow Autoencoders for Sparse Data.

Harald Steck

Proceedings of the World Wide Web Conference, 2019

Markov Random Fields for Collaborative Filtering.

Harald Steck

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Calibrated recommendations.

Harald Steck

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

2015

Interactive Recommender Systems: Tutorial.

Harald Steck, Roelof van Zwol, Chris Johnson

Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Gaussian Ranking by Matrix Factorization.

Harald Steck

Proceedings of the 9th ACM Conference on Recommender Systems, 2015

2014

A survey of collaborative filtering based social recommender systems.

Xiwang Yang, Yang Guo, Yong Liu, Harald Steck

Comput. Commun., 2014

REDD 2014 - international workshop on recommender systems evaluation: dimensions and design.

Panagiotis Adamopoulos, Alejandro Bellogín, Pablo Castells, Paolo Cremonesi, Harald Steck

Proceedings of the Eighth ACM Conference on Recommender Systems, 2014

2013

Evaluation of recommendations: rating-prediction and ranking.

Harald Steck

Proceedings of the Seventh ACM Conference on Recommender Systems, 2013

2012

Probability kernel regression for WiFi localisation.

Piotr Mirowski, Philip Whiting, Harald Steck, Ravishankar Palaniappan, Michael MacDonald, Detlef Hartmann, Tin Kam Ho

J. Locat. Based Serv., 2012

Learning the Bayesian Network Structure: Dirichlet Prior versus Data

Harald Steck

CoRR, 2012

Public Space Behavior Modeling With Video and Sensor Analytics.

Tin Kam Ho, Kim Matthews, Lawrence O'Gorman, Harald Steck

Bell Labs Tech. J., 2012

On top-k recommendation using social networks.

Xiwang Yang, Harald Steck, Yang Guo, Yong Liu

Proceedings of the Sixth ACM Conference on Recommender Systems, 2012

Circle-based recommendation in online social networks.

Xiwang Yang, Harald Steck, Yong Liu

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

2011

Multi-value probabilistic matrix factorization for IP-TV recommendations.

Yu Xin, Harald Steck

Proceedings of the 2011 ACM Conference on Recommender Systems, 2011

Item popularity and recommendation accuracy.

Harald Steck

Proceedings of the 2011 ACM Conference on Recommender Systems, 2011

KL-divergence kernel regression for non-Gaussian fingerprint based localization.

Piotr Mirowski, Harald Steck, Philip Whiting, Ravishankar Palaniappan, Michael MacDonald, Tin Kam Ho

Proceedings of the 2011 International Conference on Indoor Positioning and Indoor Navigation, 2011

2010

A Generalized Probabilistic Framework and its Variants for Training Top-k Recommender System.

Harald Steck, Yu Xin

Proceedings of the Workshop on the Practical Use of Recommender Systems, 2010

Training and testing of recommender systems on data missing not at random.

Harald Steck

Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2009

Subgroup Discovery for Test Selection: A Novel Approach and Its Application to Breast Cancer Diagnosis.

Marianne Mueller, Rómer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, Stefan Kramer

Proceedings of the Advances in Intelligent Data Analysis VIII, 2009

Data-Efficient Information-Theoretic Test Selection.

Marianne Mueller, Rómer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, Stefan Kramer

Proceedings of the Artificial Intelligence in Medicine, 2009

2008

Learning the Bayesian Network Structure: Dirichlet Prior vs Data.

Harald Steck

Proceedings of the UAI 2008, 2008

2007

Predictive Discretization during Model Selection.

Harald Steck, Tommi S. Jaakkola

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Bayesian Co-Training.

Shipeng Yu, Balaji Krishnapuram, Rómer Rosales, Harald Steck, R. Bharat Rao

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

On Ranking in Survival Analysis: Bounds on the Concordance Index.

Vikas C. Raykar, Harald Steck, Balaji Krishnapuram, Cary Dehing-Oberije, Philippe Lambin

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Automated Heart Wall Motion Abnormality Detection from Ultrasound Images Using Bayesian Networks.

Maleeha Qazi, Glenn Fung, Sriram Krishnan, Rómer Rosales, Harald Steck, R. Bharat Rao, Don Poldermans, Dhanalakshmi Chandrasekaran

Proceedings of the IJCAI 2007, 2007

Hinge Rank Loss and the Area Under the ROC Curve.

Harald Steck

Proceedings of the Machine Learning: ECML 2007, 2007

2006

Ranking by Dependence - A Fair Criteria.

Harald Steck

Proceedings of the UAI '06, 2006

2003

Bias-Corrected Bootstrap and Model Uncertainty.

Harald Steck, Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002

Unsupervised Active Learning in Large Domains.

Harald Steck, Tommi S. Jaakkola

Proceedings of the UAI '02, 2002

On the Dirichlet Prior and Bayesian Regularization.

Harald Steck, Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001

Constraint-based structural learning in Bayesian networks using finite data sets.

Harald Steck

PhD thesis, 2001

2000

On the Use of Skeletons when Learning in Bayesian Networks.

Harald Steck

Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000