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SIGECOM
2011
ACM
320views ECommerce» more  SIGECOM 2011»
13 years 3 months ago
Market making and mean reversion
Market making refers broadly to trading strategies that seek to profit by providing liquidity to other traders, while avoiding accumulating a large net position in a stock. In th...
Tanmoy Chakraborty, Michael Kearns
CSDA
2006
61views more  CSDA 2006»
14 years 14 days ago
An atmosphere-ocean time series model of global climate change
Time series models of global climate change tend to estimate a low climate-sensitivity (equilibrium effect on global temperature of doubling carbon dioxide concentrations) and a f...
David I. Stern
CSDA
2008
110views more  CSDA 2008»
14 years 15 days ago
Computing and using residuals in time series models
The most often used approaches to obtaining and using residuals in applied work with time series models, are unified and documented with both partially-known and new features. Spe...
José Alberto Mauricio
CCGRID
2010
IEEE
14 years 20 days ago
Discovering Piecewise Linear Models of Grid Workload
—Despite extensive research focused on enabling QoS for grid users through economic and intelligent resource provisioning, no consensus has emerged on the most promising strategi...
Tamás Éltetö, Cécile Ger...
HIS
2004
14 years 1 months ago
Selection of Time Series Forecasting Models based on Performance Information
In this work, we proposed to use the Zoomed Ranking approach to rank and select time series models. Zoomed Ranking, originally proposed to generate a ranking of candidate algorith...
Patrícia Maforte dos Santos, Teresa Bernard...
INFOCOM
2009
IEEE
14 years 7 months ago
Measuring Complexity and Predictability in Networks with Multiscale Entropy Analysis
—We propose to use multiscale entropy analysis in characterisation of network traffic and spectrum usage. We show that with such analysis one can quantify complexity and predict...
Janne Riihijärvi, Matthias Wellens, Petri M&a...
ICML
2006
IEEE
15 years 1 months ago
Dynamic topic models
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...
David M. Blei, John D. Lafferty