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TIT
2011
109views more  TIT 2011»
14 years 11 months ago
On Achieving Local View Capacity Via Maximal Independent Graph Scheduling
—“If we know more, we can achieve more.” This adage also applies to networks, where more information about the network state translates into higher sum-rates. In this paper, ...
Vaneet Aggarwal, Amir Salman Avestimehr, Ashutosh ...
PKDD
2009
Springer
117views Data Mining» more  PKDD 2009»
15 years 11 months ago
New Regularized Algorithms for Transductive Learning
Abstract. We propose a new graph-based label propagation algorithm for transductive learning. Each example is associated with a vertex in an undirected graph and a weighted edge be...
Partha Pratim Talukdar, Koby Crammer
ECAI
2008
Springer
15 years 6 months ago
BIDFLOW: a New Graph-Based Bidding Language for Combinatorial Auctions
In this paper we introduce a new graph based bidding language for combinatorial auctions. In our language, each bidder submits to the arbitrator a generalized flow network (netbid...
Madalina Croitoru, Cornelius Croitoru, Paul H. Lew...
IJCAI
2007
15 years 6 months ago
Graph-Based Semi-Supervised Learning as a Generative Model
This paper proposes and develops a new graph-based semi-supervised learning method. Different from previous graph-based methods that are based on discriminative models, our method...
Jingrui He, Jaime G. Carbonell, Yan Liu 0002
JMLR
2010
159views more  JMLR 2010»
14 years 11 months ago
Semi-Supervised Learning with Max-Margin Graph Cuts
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
Branislav Kveton, Michal Valko, Ali Rahimi, Ling H...