Harald Steck

发表

Interactive Recommender Systems: Tutorial

Harald Steck, Roelof van Zwol, Chris Johnson, 2015, RecSys.

Learning the Bayesian Network Structure: Dirichlet Prior versus Data pdf

Harald Steck, H. Steck, 2008, UAI 2008.

of the Workshop on Recommendation Utility Evaluation : Beyond RMSE ( RUE 2011 ) held at the 6 th ACM International Conference on Recommender Systems ( RecSys 2012 ) 9 September 2012 Dublin , Ireland

Christian Posse, Pablo Castells, Harald Steck, 2012 .

A survey of collaborative filtering based social recommender systems

Yang Guo, Yong Liu, Harald Steck, 2014, Comput. Commun..

On Ranking in Survival Analysis: Bounds on the Concordance Index

Balaji Krishnapuram, Harald Steck, Vikas C. Raykar, 2007, NIPS.

Circle-based recommendation in online social networks

Harald Steck, Xiwang Yang, Yong Liu, 2012, KDD.

Evaluation of recommendations: rating-prediction and ranking

Harald Steck, H. Steck, 2013, RecSys.

On the Use of Skeletons when Learning in Bayesian Networks

Harald Steck, 2000, UAI.

Multi-value probabilistic matrix factorization for IP-TV recommendations

Yu Xin, Harald Steck, 2011, RecSys '11.

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

Glenn Fung, Rómer Rosales, R. Bharat Rao, 2007, IJCAI.

Probability kernel regression for WiFi localisation

Tin Kam Ho, Michael MacDonald, Phil Whiting, 2012, J. Locat. Based Serv..

Unsupervised Active Learning in Large Domains

Tommi S. Jaakkola, Harald Steck, T. Jaakkola, 2002, UAI.

Ranking by Dependence - A Fair Criteria pdf

Harald Steck, 2006, UAI.

Harald Steck, H. Steck, 2011, RecSys '11.

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

Rómer Rosales, Stefan Kramer, R. Bharat Rao, 2009, IDA.

Learning the Bayesian Network Structure: Dirichlet Prior vs Data

Harald Steck, H. Steck, 2008, UAI.

Collaborative Filtering via High-Dimensional Regression pdf

Harald Steck, 2019, ArXiv.

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

Harald Steck, H. Steck, 2001 .

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

Harald Steck, H. Steck, 2010, KDD.

On top-k recommendation using social networks

Yang Guo, Yong Liu, Harald Steck, 2012, RecSys.

Public space behavior modeling with video and sensor analytics

Tin Kam Ho, Harald Steck, Lawrence O'Gorman, 2012, Bell Labs Technical Journal.

Markov Random Fields for Collaborative Filtering

Harald Steck, H. Steck, 2019, NeurIPS.

Bias-Corrected Bootstrap and Model Uncertainty

Tommi S. Jaakkola, Harald Steck, T. Jaakkola, 2003, NIPS.

Random signature testing procedure: A new method to verify the prognostic performance of gene signatures

Glenn Fung, Harald Steck, Philippe Lambin, 2008 .

Predictive Discretization during Model Selection

Tommi S. Jaakkola, Harald Steck, T. Jaakkola, 2004, AISTATS.

Data-Efficient Information-Theoretic Test Selection

Rómer Rosales, Stefan Kramer, R. Bharat Rao, 2009, AIME.

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

Tin Kam Ho, Michael MacDonald, Phil Whiting, 2011, 2011 International Conference on Indoor Positioning and Indoor Navigation.

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

Yu Xin, Harald Steck, Yu Xin, 2010, PRSAT@RecSys.

Embarrassingly Shallow Autoencoders for Sparse Data

Harald Steck, H. Steck, 2019, WWW.

On the Dirichlet Prior and Bayesian Regularization

Tommi S. Jaakkola, Harald Steck, T. Jaakkola, 2002, NIPS.

Autoencoders that don't overfit towards the Identity

Harald Steck, H. Steck, 2020, NeurIPS.

Hinge Rank Loss and the Area Under the ROC Curve

Harald Steck, H. Steck, 2007, ECML.

Gaussian Ranking by Matrix Factorization

Harald Steck, H. Steck, 2015, RecSys.

Calibrated recommendations

Harald Steck, H. Steck, 2018, RecSys.

Ontologies medicales pour soutenir une decision clinique assistee par ordinateur

R. Bharat Rao, Harald Steck, Romer Rosales, 2006 .

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

Panagiotis Adamopoulos, Alejandro Bellogín, Pablo Castells, 2014, RecSys '14.

ADMM SLIM: Sparse Recommendations for Many Users

Harald Steck, Tony Jebara, Maria Dimakopoulou, 2020, WSDM.

Autonomous RF Surveying Robot for Indoor Localization and Tracking

Philip A. Whiting, Tin Kam Ho, Michael MacDonald, 2011 .

On the Regularization of Autoencoders pdf

Harald Steck, Dario García-García, H. Steck, 2021, ArXiv.

Deep Learning for Recommender Systems: A Netflix Case Study

Justin Basilico, Linas Baltrunas, Dawen Liang, 2022, AI Mag..

( Semi-) Predictive Discretization During Model Selection

Harald Steck, 2003 .

A Simple but Highly Effective Approach to Evaluate the Prognostic Performance of Gene Expression Signatures

Glenn Fung, Harald Steck, Philippe Lambin, 2011, PloS one.

2488: Combining Clinical Data With Medical Knowledge Improves Prediction Models for NSCLC After (Chemo) Radiotherapy

Harald Steck, Philippe Lambin, Dirk De Ruysscher, 2006 .