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ICDE
2007
IEEE
110views Database» more  ICDE 2007»
16 years 1 months ago
Embedding Emotional Context in Recommender Systems
Emotional context is becoming a promising paradigm to develop more intuitive and sensitive recommender systems. Ambient Recommender Systems, arise from the analysis of new trends ...
Gustavo González, Josep Lluís de la ...
IJCAI
2007
15 years 8 months ago
Improving Embeddings by Flexible Exploitation of Side Information
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
Ali Ghodsi, Dana F. Wilkinson, Finnegan Southey
WSDM
2012
ACM
259views Data Mining» more  WSDM 2012»
14 years 2 months ago
Learning recommender systems with adaptive regularization
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
Steffen Rendle
KDD
2009
ACM
132views Data Mining» more  KDD 2009»
16 years 7 months ago
Learning patterns in the dynamics of biological networks
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
Chang Hun You, Lawrence B. Holder, Diane J. Cook
RECOMB
2007
Springer
16 years 7 months ago
Minimizing and Learning Energy Functions for Side-Chain Prediction
Abstract. Side-chain prediction is an important subproblem of the general protein folding problem. Despite much progress in side-chain prediction, performance is far from satisfact...
Chen Yanover, Ora Schueler-Furman, Yair Weiss