163 citations · 184 across the 6 of their papers we have counts for
6 papers · 1 filter
Robust Neural Regression via Uncertainty Learning
Akib Mashrur, Wei Luo, Nayyar A. Zaidi +1
Deep neural networks tend to underestimate uncertainty and produce overly confident predictions. Recently proposed solutions, such as MC Dropout and SDENet, require complex trainin…
Proximity Forest: An effective and scalable distance-based classifier for time series
Benjamin Lucas, Ahmed Shifaz, Charlotte Pelletier +5
Research into the classification of time series has made enormous progress in the last decade. The UCR time series archive has played a significant role in challenging and guiding…
On the Inter-relationships among Drift rate, Forgetting rate, Bias/variance profile and Error
Nayyar A. Zaidi, Geoffrey I. Webb, Francois Petitjean +1
We propose two general and falsifiable hypotheses about expectations on generalization error when learning in the context of concept drift. One posits that as drift rate increases,…
Accurate parameter estimation for Bayesian Network Classifiers using Hierarchical Dirichlet Processes
Francois Petitjean, Wray Buntine, Geoffrey I. Webb +1
This paper introduces a novel parameter estimation method for the probability tables of Bayesian network classifiers (BNCs), using hierarchical Dirichlet processes (HDPs). The main…
On the Effectiveness of Discretizing Quantitative Attributes in Linear Classifiers
Nayyar A. Zaidi, Yang Du, Geoffrey I. Webb
Learning algorithms that learn linear models often have high representation bias on real-world problems. In this paper, we show that this representation bias can be greatly reduced…
Deep Broad Learning - Big Models for Big Data
Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman +1
Deep learning has demonstrated the power of detailed modeling of complex high-order (multivariate) interactions in data. For some learning tasks there is power in learning models t…