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» Introduction to Randomized Algorithms
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TIT
2002
129views more  TIT 2002»
15 years 5 months ago
Arbitrary source models and Bayesian codebooks in rate-distortion theory
-- We characterize the best achievable performance of lossy compression algorithms operating on arbitrary random sources, and with respect to general distortion measures. Direct an...
Ioannis Kontoyiannis, Junshan Zhang
TIST
2011
136views more  TIST 2011»
15 years 1 months ago
Probabilistic models for concurrent chatting activity recognition
Recognition of chatting activities in social interactions is useful for constructing human social networks. However, the existence of multiple people involved in multiple dialogue...
Jane Yung-jen Hsu, Chia-chun Lian, Wan-rong Jih
JMLR
2010
151views more  JMLR 2010»
15 years 1 months ago
Understanding the difficulty of training deep feedforward neural networks
Whereas before 2006 it appears that deep multilayer neural networks were not successfully trained, since then several algorithms have been shown to successfully train them, with e...
Xavier Glorot, Yoshua Bengio
AAAI
2011
14 years 6 months ago
Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation
Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...
Marion Neumann, Babak Ahmadi, Kristian Kersting
PDCAT
2005
Springer
15 years 11 months ago
Optimal Routing in a Small-World Network
Recently a bulk of research [14, 5, 15, 9] has been done on the modelling of the smallworld phenomenon, which has been shown to be pervasive in social and nature networks, and eng...
Jianyang Zeng, Wen-Jing Hsu