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BMCBI
2010
152views more  BMCBI 2010»
13 years 9 months ago
Comparative study of three commonly used continuous deterministic methods for modeling gene regulation networks
Background: A gene-regulatory network (GRN) refers to DNA segments that interact through their RNA and protein products and thereby govern the rates at which genes are transcribed...
Martin T. Swain, Johannes J. Mandel, Werner Dubitz...
SAINT
2005
IEEE
14 years 2 months ago
On Scalable Modeling of TCP Congestion Control Mechanism for Large-Scale IP Networks
In this paper, we propose an analytic approach of modeling a closed-loop network with multiple feedback loops using fluid-flow approximation. Specifically, we model building bl...
Hiroyuki Ohsaki, Juñya Ujiie, Makoto Imase
AAAI
2011
12 years 9 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
ESWA
2010
118views more  ESWA 2010»
13 years 7 months ago
Integrating independent component analysis-based denoising scheme with neural network for stock price prediction
The forecasting of stock price is one of the most challenging tasks in investment/financial decision-making since stock prices/indices are inherently noisy and non-stationary. In ...
Chi-Jie Lu
VLDB
2007
ACM
122views Database» more  VLDB 2007»
14 years 9 months ago
MIST: Distributed Indexing and Querying in Sensor Networks using Statistical Models
The modeling of high level semantic events from low level sensor signals is important in order to understand distributed phenomena. For such content-modeling purposes, transformat...
Arnab Bhattacharya, Anand Meka, Ambuj K. Singh