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,...
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...
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...
Abstract. We investigated the network topology organized through spike-timingdependent plasticity (STDP) using pair- and triad-connectivity patterns, considering di erence of excit...
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...