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ICA
2007
Springer
14 years 5 months ago
Discovering Convolutive Speech Phones Using Sparseness and Non-negativity
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can b...
Paul D. O'Grady, Barak A. Pearlmutter
JMLR
2012
12 years 1 months ago
Primal-Dual methods for sparse constrained matrix completion
We develop scalable algorithms for regular and non-negative matrix completion. In particular, we base the methods on trace-norm regularization that induces a low rank predicted ma...
Yu Xin, Tommi Jaakkola
RECSYS
2010
ACM
13 years 8 months ago
List-wise learning to rank with matrix factorization for collaborative filtering
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
Yue Shi, Martha Larson, Alan Hanjalic
ICPR
2000
IEEE
14 years 3 months ago
A General Rank-2 Parameterization of the Fundamental Matrix
All the methods for estimating the fundamental matrix do not naturally exploit the rank-2 constraint. For these reason some few rank-2 parameterizations of the fundamental matrix ...
Francesco Isgrò, Emanuele Trucco
KDD
2012
ACM
201views Data Mining» more  KDD 2012»
12 years 1 months ago
Low rank modeling of signed networks
Trust networks, where people leave trust and distrust feedback, are becoming increasingly common. These networks may be regarded as signed graphs, where a positive edge weight cap...
Cho-Jui Hsieh, Kai-Yang Chiang, Inderjit S. Dhillo...