Enes Makalic

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A spoken language interpretation component for a robot dialogue system

Ingrid Zukerman, Michael Niemann, Enes Makalic, 2008, INTERSPEECH.

MML Invariant Linear Regression

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2009, Australasian Conference on Artificial Intelligence.

MML Logistic Regression with Translation and Rotation Invariant Priors

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2012, Australasian Conference on Artificial Intelligence.

The Consistency of MDL for Linear Regression Models With Increasing Signal-to-Noise Ratio

Enes Makalic, Daniel F. Schmidt, 2012, IEEE Transactions on Signal Processing.

Bayesian Robust Regression with the Horseshoe+ Estimator

Enes Makalic, Daniel F. Schmidt, John L. Hopper, 2016, Australasian Conference on Artificial Intelligence.

MMLD Inference of Multilayer Perceptrons

Enes Makalic, Lloyd Allison, 2011, Algorithmic Probability and Friends.

Adaptive Bayesian Shrinkage Estimation Using Log-Scale Shrinkage Priors pdf

Enes Makalic, Daniel F. Schmidt, 2018, ArXiv.

Supercomputing enabling exhaustive statistical analysis of genome wide association study data: Preliminary results

Enes Makalic, Matthias Reumann, Daniel F. Schmidt, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Minimum Message Length Analysis of the Behrens-Fisher Problem

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2013, Algorithmic Probability and Friends.

MML inference of RBF neural networks for regression

Enes Makalic, Lloyd Allison, Andrew P. Paplinski, 2004 .

Bayesian Generalized Horseshoe Estimation of Generalized Linear Models

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2019, ECML/PKDD.

A Simple Bayesian Algorithm for Feature Ranking in High Dimensional Regression Problems

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2011, Australasian Conference on Artificial Intelligence.

A Probabilistic Model for Understanding Composite Spoken Descriptions

Ingrid Zukerman, Michael Niemann, Enes Makalic, 2008, PRICAI.

A Simple Sampler for the Horseshoe Estimator

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2015, IEEE Signal Processing Letters.

Using Probabilistic Feature Matching to Understand Spoken Descriptions

Ingrid Zukerman, Michael Niemann, Enes Makalic, 2008, Australasian Conference on Artificial Intelligence.

Universal Models for the Exponential Distribution

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2009, IEEE Transactions on Information Theory.

Minimum Message Length Ridge Regression for Generalized Linear Models

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2013, Australasian Conference on Artificial Intelligence.

Towards the Interpretation of Utterance Sequences in a Dialogue System

Ingrid Zukerman, Enes Makalic, Kapil Kumar Gupta, 2009, SIGDIAL Conference.

Minimum Message Length Inference and Mixture Modelling of Inverse Gaussian Distributions

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2012, Australasian Conference on Artificial Intelligence.

MML Inference of Single-layer Neural Networks

Enes Makalic, David L. Dowe, Lloyd Allison, 2003 .

The Behaviour of the Akaike Information Criterion When Applied to Non-nested Sequences of Models

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2010, Australasian Conference on Artificial Intelligence.

Hypothesis Generation and Maintenance in the Interpretation of Spoken Utterances

Ingrid Zukerman, Sarah George, Michael Niemann, 2007, Australian Conference on Artificial Intelligence.

Robust Lasso Regression with Student-t Residuals

Enes Makalic, Daniel F. Schmidt, 2017, Australasian Conference on Artificial Intelligence.

A Probabilistic Approach to the Interpretation of Spoken Utterances

Ingrid Zukerman, Sarah George, Michael Niemann, 2008, PRICAI.

DEPTH: A Novel Algorithm for Feature Ranking with Application to Genome-Wide Association Studies

Enes Makalic, Daniel F. Schmidt, John L. Hopper, 2013, Australasian Conference on Artificial Intelligence.

Estimating the Order of an Autoregressive Model Using Normalized Maximum Likelihood

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2011, IEEE Transactions on Signal Processing.

Approximating Message Lengths of Hierarchical Bayesian Models Using Posterior Sampling

Enes Makalic, Daniel F. Schmidt, John L. Hopper, 2016, Australasian Conference on Artificial Intelligence.

Fast Computation of the Kullback–Leibler Divergence and Exact Fisher Information for the First-Order Moving Average Model

Enes Makalic, Daniel F. Schmidt, 2010, IEEE Signal Processing Letters.

Bayesian Grouped Horseshoe Regression with Application to Additive Models

Enes Makalic, Daniel F. Schmidt, Guoqi Qian, 2016, Australasian Conference on Artificial Intelligence.

SPARK: An Open-Source Knowledge Discovery Platform That Leverages Non-Relational Databases and Massively Parallel Computational Power for Heterogeneous Genomic Datasets

Enes Makalic, John L. Hopper, Adrian Bickerstaffe, 2016 .

Review of Modern Logistic Regression Methods with Application to Small and Medium Sample Size Problems

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2010, Australasian Conference on Artificial Intelligence.

MML Classification of Music Genres

Enes Makalic, Adrian C. Bickerstaffe, E. Makalic, 2003, Australian Conference on Artificial Intelligence.

Logistic Regression with the Nonnegative Garrote

Enes Makalic, Daniel F. Schmidt, E. Makalic, 2011, Australasian Conference on Artificial Intelligence.