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» Algorithms for Challenging Motif Problems
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NIPS
2007
15 years 6 months ago
Convex Clustering with Exemplar-Based Models
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
Danial Lashkari, Polina Golland
142
Voted
ICML
2010
IEEE
15 years 5 months ago
Online Streaming Feature Selection
We study an interesting and challenging problem, online streaming feature selection, in which the size of the feature set is unknown, and not all features are available for learni...
Xindong Wu, Kui Yu, Hao Wang, Wei Ding
151
Voted
DEXA
2010
Springer
182views Database» more  DEXA 2010»
15 years 4 months ago
Minimum Spanning Tree on Spatio-Temporal Networks
Given a spatio-temporal network (ST network) whose edge properties vary with time, a time-sub-interval minimum spanning tree (TSMST) is a collection of distinct minimum spanning t...
Viswanath Gunturi, Shashi Shekhar, Arnab Bhattacha...
TWC
2008
152views more  TWC 2008»
15 years 4 months ago
Bandwidth-Guaranteed Fair Scheduling with Effective Excess Bandwidth Allocation for Wireless Networks
Traffic scheduling is key to the provision of quality of service (QoS) differentiation and guarantees in wireless networks. Unlike its wireline counterpart, wireless communications...
Yaxin Cao, Ka-Cheong Leung, Victor O. K. Li
127
Voted
AI
2000
Springer
15 years 4 months ago
Credal networks
Credal networks are models that extend Bayesian nets to deal with imprecision in probability, and can actually be regarded as sets of Bayesian nets. Evidence suggests that credal ...
Fabio Gagliardi Cozman