4 citations · 9 across the 8 of their papers we have counts for
8 papers
The role of prior information and computational power in Machine Learning
Diego Marcondes, Adilson Simonis, Junior Barrera
Science consists on conceiving hypotheses, confronting them with empirical evidence, and keeping only hypotheses which have not yet been falsified. Under deductive reasoning they a…
Learning the hypotheses space from data through a U-curve algorithm
Diego Marcondes, Adilson Simonis, Junior Barrera
This paper proposes a data-driven systematic, consistent and non-exhaustive approach to Model Selection, that is an extension of the classical agnostic PAC learning model. In this…
Learning the Hypotheses Space from data Part II: Convergence and Feasibility
Diego Marcondes, Adilson Simonis, Junior Barrera
In part \textit{I} we proposed a structure for a general Hypotheses Space , the Learning Space , which can be employed to avoid \textit{overfi…
Learning the Hypotheses Space from data: Learning Space and U-curve Property
Diego Marcondes, Adilson Simonis, Junior Barrera
This paper presents an extension of the classical agnostic PAC learning model in which learning problems are modelled not only by a Hypothesis Space , but also by a Le…
Feature Selection based on the Local Lift Dependence Scale
Diego Marcondes, Adilson Simonis, Junior Barrera
This paper uses a classical approach to feature selection: minimization of a cost function applied on estimated joint distributions. However, the search space in which such minimiz…
The U-curve optimization problem: improvements on the original algorithm and time complexity analysis
Marcelo S. Reis, Carlos E. Ferreira, Junior Barrera
The U-curve optimization problem is characterized by a decomposable in U-shaped curves cost function over the chains of a Boolean lattice. This problem can be applied to model the…