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SIGECOM
2010
ACM
149views ECommerce» more  SIGECOM 2010»
14 years 16 days ago
A new understanding of prediction markets via no-regret learning
We explore the striking mathematical connections that exist between market scoring rules, cost function based prediction markets, and no-regret learning. We first show that any c...
Yiling Chen, Jennifer Wortman Vaughan
BMCBI
2011
12 years 11 months ago
BICEPP: an example-based statistical text mining method for predicting the binary characteristics of drugs
Background: The identification of drug characteristics is a clinically important task, but it requires much expert knowledge and consumes substantial resources. We have developed ...
Frank P. Y. Lin, Stephen Anthony, Thomas M. Polase...
ISCA
2000
IEEE
121views Hardware» more  ISCA 2000»
14 years 3 days ago
Selective, accurate, and timely self-invalidation using last-touch prediction
Communication in cache-coherent distributed shared memory (DSM) often requires invalidating (or writing back) cached copies of a memory block, incurring high overheads. This paper...
An-Chow Lai, Babak Falsafi
SOCO
2002
Springer
13 years 7 months ago
Granular neural web agents for stock prediction
A granular neural Web-based stock prediction agent is developed using the granular neural network (GNN) that can discover fuzzy rules. Stock data sets are downloaded from www.yahoo...
Yan-Qing Zhang, Somasheker Akkaladevi, George J. V...
GECCO
2004
Springer
166views Optimization» more  GECCO 2004»
14 years 1 months ago
Evolutionary Ensemble for Stock Prediction
We propose a genetic ensemble of recurrent neural networks for stock prediction model. The genetic algorithm tunes neural networks in a two-dimensional and parallel framework. The ...
Yung-Keun Kwon, Byung Ro Moon