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108
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ICDM
2007
IEEE
106views Data Mining» more  ICDM 2007»
15 years 8 months ago
High-Speed Function Approximation
We address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on mod...
Biswanath Panda, Mirek Riedewald, Johannes Gehrke,...
128
Voted
PKDD
2007
Springer
146views Data Mining» more  PKDD 2007»
15 years 8 months ago
A Method for Multi-relational Classification Using Single and Multi-feature Aggregation Functions
This paper presents a novel method for multi-relational classification via an aggregation-based Inductive Logic Programming (ILP) approach. We extend the classical ILP representati...
Richard Frank, Flavia Moser, Martin Ester
AAAI
2008
15 years 4 months ago
Strategyproof Classification under Constant Hypotheses: A Tale of Two Functions
We consider the following setting: a decision maker must make a decision based on reported data points with binary labels. Subsets of data points are controlled by different selfi...
Reshef Meir, Ariel D. Procaccia, Jeffrey S. Rosens...
132
Voted
ICONIP
2010
14 years 12 months ago
Emergence of Highly Nonrandom Functional Synaptic Connectivity Through STDP
Abstract. We investigated the network topology organized through spike-timingdependent plasticity (STDP) using pair- and triad-connectivity patterns, considering di erence of excit...
Hideyuki Kato, Tohru Ikeguchi
TNN
2010
216views Management» more  TNN 2010»
14 years 9 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok