Fab: content-based, collaborative recommendation
Communications of the ACM
A view of the EM algorithm that justifies incremental, sparse, and other variants
Proceedings of the NATO Advanced Study Institute on Learning in graphical models
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Methods and metrics for cold-start recommendations
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Fast maximum margin matrix factorization for collaborative prediction
ICML '05 Proceedings of the 22nd international conference on Machine learning
Naïve filterbots for robust cold-start recommendations
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Efficient bayesian hierarchical user modeling for recommendation system
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Predictive discrete latent factor models for large scale dyadic data
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Modeling relationships at multiple scales to improve accuracy of large recommender systems
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation
The Journal of Machine Learning Research
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Proceedings of the 25th international conference on Machine learning
Spatio-temporal models for estimating click-through rate
Proceedings of the 18th international conference on World wide web
A spatio-temporal approach to collaborative filtering
Proceedings of the third ACM conference on Recommender systems
Pairwise preference regression for cold-start recommendation
Proceedings of the third ACM conference on Recommender systems
fLDA: matrix factorization through latent dirichlet allocation
Proceedings of the third ACM international conference on Web search and data mining
Estimating rates of rare events with multiple hierarchies through scalable log-linear models
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Fast online learning through offline initialization for time-sensitive recommendation
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
SCOAL: A framework for simultaneous co-clustering and learning from complex data
ACM Transactions on Knowledge Discovery from Data (TKDD)
Adaptive bootstrapping of recommender systems using decision trees
Proceedings of the fourth ACM international conference on Web search and data mining
Enhanced email spam filtering through combining similarity graphs
Proceedings of the fourth ACM international conference on Web search and data mining
Like like alike: joint friendship and interest propagation in social networks
Proceedings of the 20th international conference on World wide web
Collaborative competitive filtering: learning recommender using context of user choice
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Functional matrix factorizations for cold-start recommendation
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Fast context-aware recommendations with factorization machines
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Recommending ephemeral items at web scale
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Multiple domain user personalization
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Response prediction using collaborative filtering with hierarchies and side-information
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Collaborative topic modeling for recommending scientific articles
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Localized factor models for multi-context recommendation
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Cost-aware travel tour recommendation
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
I want to answer; who has a question?: Yahoo! answers recommender system
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 2011 workshop on Data mining for medicine and healthcare
Link prediction via matrix factorization
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Generalizing matrix factorization through flexible regression priors
Proceedings of the fifth ACM conference on Recommender systems
Yahoo! music recommendations: modeling music ratings with temporal dynamics and item taxonomy
Proceedings of the fifth ACM conference on Recommender systems
Multi-value probabilistic matrix factorization for IP-TV recommendations
Proceedings of the fifth ACM conference on Recommender systems
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Overcoming browser cookie churn with clustering
Proceedings of the fifth ACM international conference on Web search and data mining
To each his own: personalized content selection based on text comprehensibility
Proceedings of the fifth ACM international conference on Web search and data mining
Finding the right consumer: optimizing for conversion in display advertising campaigns
Proceedings of the fifth ACM international conference on Web search and data mining
Personalized recommendation of user comments via factor models
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Factorization Machines with libFM
ACM Transactions on Intelligent Systems and Technology (TIST)
Build your own music recommender by modeling internet radio streams
Proceedings of the 21st international conference on World Wide Web
Targeting converters for new campaigns through factor models
Proceedings of the 21st international conference on World Wide Web
Sparse linear methods with side information for Top-N recommendations
Proceedings of the 21st international conference companion on World Wide Web
Expert Systems with Applications: An International Journal
Challenging the long tail recommendation
Proceedings of the VLDB Endowment
Supercharging recommender systems using taxonomies for learning user purchase behavior
Proceedings of the VLDB Endowment
Feature enriched nonparametric bayesian co-clustering
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
TFMAP: optimizing MAP for top-n context-aware recommendation
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Adaptive diversification of recommendation results via latent factor portfolio
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Personalized click shaping through lagrangian duality for online recommendation
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Learning to rank social update streams
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Collaborative personalized tweet recommendation
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
A propagation model for integrating web of things and social networks
ICSOC'11 Proceedings of the 2011 international conference on Service-Oriented Computing
CLiMF: learning to maximize reciprocal rank with collaborative less-is-more filtering
Proceedings of the sixth ACM conference on Recommender systems
Sparse linear methods with side information for top-n recommendations
Proceedings of the sixth ACM conference on Recommender systems
LogUCB: an explore-exploit algorithm for comments recommendation
Proceedings of the 21st ACM international conference on Information and knowledge management
Multi-faceted ranking of news articles using post-read actions
Proceedings of the 21st ACM international conference on Information and knowledge management
PENETRATE: Personalized news recommendation using ensemble hierarchical clustering
Expert Systems with Applications: An International Journal
News recommendation via hypergraph learning: encapsulation of user behavior and news content
Proceedings of the sixth ACM international conference on Web search and data mining
Latent factor models with additive and hierarchically-smoothed user preferences
Proceedings of the sixth ACM international conference on Web search and data mining
Learning multiple-question decision trees for cold-start recommendation
Proceedings of the sixth ACM international conference on Web search and data mining
Connecting comments and tags: improved modeling of social tagging systems
Proceedings of the sixth ACM international conference on Web search and data mining
Co-factorization machines: modeling user interests and predicting individual decisions in Twitter
Proceedings of the sixth ACM international conference on Web search and data mining
Retweet or not?: personalized tweet re-ranking
Proceedings of the sixth ACM international conference on Web search and data mining
Content recommendation on web portals
Communications of the ACM
Learning geographical preferences for point-of-interest recommendation
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
DIGTOBI: a recommendation system for Digg articles using probabilistic modeling
Proceedings of the 22nd international conference on World Wide Web
GAPfm: optimal top-n recommendations for graded relevance domains
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Scientific articles recommendation
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Context-aware review helpfulness rating prediction
Proceedings of the 7th ACM conference on Recommender systems
CUDIA: Probabilistic cross-level imputation using individual auxiliary information
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Hierarchical Bayesian matrix factorization with side information
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Celebrity recommendation with collaborative social topic regression
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Taxonomy discovery for personalized recommendation
Proceedings of the 7th ACM international conference on Web search and data mining
Cost-Aware Collaborative Filtering for Travel Tour Recommendations
ACM Transactions on Information Systems (TOIS)
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We propose a novel latent factor model to accurately predict response for large scale dyadic data in the presence of features. Our approach is based on a model that predicts response as a multiplicative function of row and column latent factors that are estimated through separate regressions on known row and column features. In fact, our model provides a single unified framework to address both cold and warm start scenarios that are commonplace in practical applications like recommender systems, online advertising, web search, etc. We provide scalable and accurate model fitting methods based on Iterated Conditional Mode and Monte Carlo EM algorithms. We show our model induces a stochastic process on the dyadic space with kernel (covariance) given by a polynomial function of features. Methods that generalize our procedure to estimate factors in an online fashion for dynamic applications are also considered. Our method is illustrated on benchmark datasets and a novel content recommendation application that arises in the context of Yahoo! Front Page. We report significant improvements over several commonly used methods on all datasets.