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» Lattice problems and norm embeddings
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DAM
2011
13 years 3 months ago
Weak sense of direction labelings and graph embeddings
An edge-labeling λ for a directed graph G has a weak sense of direction (WSD) if there is a function f that satisfies the condition that for any node u and for any two label seq...
Christine T. Cheng, Ichiro Suzuki
CORR
2011
Springer
176views Education» more  CORR 2011»
13 years 3 months ago
Decoding by Embedding: Correct Decoding Radius and DMT Optimality
—In lattice-coded multiple-input multiple-output (MIMO) systems, optimal decoding amounts to solving the closest vector problem (CVP). Embedding is a powerful technique for the a...
Cong Ling, Shuiyin Liu, Laura Luzzi, Damien Stehl&...
CORR
2010
Springer
167views Education» more  CORR 2010»
13 years 8 months ago
Network Flow Algorithms for Structured Sparsity
We consider a class of learning problems that involve a structured sparsityinducing norm defined as the sum of -norms over groups of variables. Whereas a lot of effort has been pu...
Julien Mairal, Rodolphe Jenatton, Guillaume Obozin...
PAMI
2006
206views more  PAMI 2006»
13 years 8 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
IJCV
2006
115views more  IJCV 2006»
13 years 8 months ago
Object Recognition as Many-to-Many Feature Matching
Object recognition can be formulated as matching image features to model features. When recognition is exemplar-based, feature correspondence is one-to-one. However, segmentation e...
M. Fatih Demirci, Ali Shokoufandeh, Yakov Keselman...