no code implementations • 14 Mar 2024 • Dhurim Cakiqi, Max A. Little
Our description is given entirely in terms of the non-parametric ADMG structure specifying a causal model and the algebraic signature of the corresponding monoidal category, to which a sequence of manipulations is then applied so as to arrive at a modified monoidal category in which the desired, purely syntactic interventional causal model, is obtained.
no code implementations • 21 Jun 2023 • Xi He, Waheed Ul Rahman, Max A. Little
We demonstrate the effectiveness of this algorithm on synthetic and real-world datasets, showing optimal accuracy both in and out-of-sample, in practical computational time.
no code implementations • 7 Aug 2022 • Zaifa Xue, Huibin Lu, Tao Zhang, Max A. Little
Therefore, this paper proposes a patient-specific game-based transfer (PSGT) method for PD severity prediction.
no code implementations • 5 Jul 2021 • Max A. Little, Xi He, Ugur Kayas
Dynamic programming (DP) is an algorithmic design paradigm for the efficient, exact solution of otherwise intractable, combinatorial problems.
no code implementations • 7 Feb 2021 • Yazan Qarout, Yordan P. Raykov, Max A. Little
We propose a robust framework for interpretable, few-shot analysis of non-stationary sequential data based on flexible graphical models to express the structured distribution of sequential events, using prototype radial basis function (RBF) neural network emissions.
no code implementations • 2 Sep 2020 • Wasifur Rahman, Sangwu Lee, Md. Saiful Islam, Victor Nikhil Antony, Harshil Ratnu, Mohammad Rafayet Ali, Abdullah Al Mamun, Ellen Wagner, Stella Jensen-Roberts, Max A. Little, Ray Dorsey, Ehsan Hoque
In this paper, we envision a web-based framework that can help anyone, anywhere around the world record a short speech task, and analyze the recorded data to screen for Parkinson's disease (PD).
no code implementations • 22 Jun 2020 • Adam Farooq, Yordan P. Raykov, Petar Raykov, Max A. Little
Ubiquitous linear Gaussian exploratory tools such as principle component analysis (PCA) and factor analysis (FA) remain widely used as tools for: exploratory analysis, pre-processing, data visualization and related tasks.
no code implementations • 21 Oct 2019 • Max A. Little, Reham Badawy
However, these techniques are often incompatible with modern, nonparametric machine learning algorithms since they typically require explicit probabilistic models.
no code implementations • 27 May 2019 • Adam Farooq, Yordan P. Raykov, Luc Evers, Max A. Little
Using the linear Gaussian latent variable model as a starting point we relax some of the constraints it imposes by deriving a nonparametric latent feature Gaussian variable model.
no code implementations • 21 May 2019 • Liming Shi, Jesper Kjaer Nielsen, Jesper Rindom Jensen, Max A. Little, Mads Graesboll Christensen
In this paper, a fully Bayesian fundamental frequency tracking algorithm based on the harmonic model and a first-order Markov process model is proposed.
2 code implementations • 5 Jan 2016 • Andong Zhan, Max A. Little, Denzil A. Harris, Solomon O. Abiola, E. Ray Dorsey, Suchi Saria, Andreas Terzis
Objective: The aim of this study is to develop a smartphone-based high-frequency remote monitoring platform, assess its feasibility for remote monitoring of symptoms in Parkinson's disease, and demonstrate the value of data collected using the platform by detecting dopaminergic medication response.
Computers and Society
no code implementations • 4 Nov 2014 • Yordan P. Raykov, Alexis Boukouvalas, Max A. Little
This is a well-posed approximation to the MAP solution of the probabilistic DPM model.
1 code implementation • Journal of the Royal Society Interface 2013 • Ben D. Fulcher, Max A. Little, Nick S. Jones
This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines, and automate the selection of useful methods for time-series classification and regression tasks.