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Found 9 papers, 4 papers with code
Handling Overlapping Asymmetric Datasets -- A Twice Penalized P-Spline Approach
Common solutions such as missing imputation can often be unwise if the smaller cohort is significantly different in scale to the larger sample, therefore the aim of this research is to develop a new method which can model the smaller cohort against a particular response, whilst considering the larger cohort also.
ConvBoost: Boosting ConvNets for Sensor-based Activity Recognition
Specifically, with the introduction of three conceptual layers--Sampling Layer, Data Augmentation Layer, and Resilient Layer -- we develop three "boosters" -- R-Frame, Mix-up, and C-Drop -- to enrich the per-epoch training data by dense-sampling, synthesizing, and simulating, respectively.
Simple Yet Surprisingly Effective Training Strategies for LSTMs in Sensor-Based Human Activity Recognition
What remains a major challenge though is the sporadic activity recognition (SAR) problem, where activities of interest tend to be non periodic, and occur less frequently when compared with the often large amount of irrelevant background activities.
Benchmark time series data sets for PyTorch -- the torchtime package
The development of models for Electronic Health Record data is an area of active research featuring a small number of public benchmark data sets.
Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context
As a consequence, we survey in this paper the main technologies with respect to all four of the FEAS properties, for data-centric as well as model-centric stages of the machine learning system life cycle.
Building Rule Hierarchies for Efficient Logical Rule Learning from Knowledge Graphs
Many systems have been developed in recent years to mine logical rules from large-scale Knowledge Graphs (KGs), on the grounds that representing regularities as rules enables both the interpretable inference of new facts, and the explanation of known facts.
Towards Learning Instantiated Logical Rules from Knowledge Graphs
Instantiated rules contain constants extracted from KGs.
A customisable pipeline for continuously harvesting socially-minded Twitter users
On social media platforms and Twitter in particular, specific classes of users such as influencers have been given satisfactory operational definitions in terms of network and content metrics.
Recruiting from the network: discovering Twitter users who can help combat Zika epidemics
Tropical diseases like \textit{Chikungunya} and \textit{Zika} have come to prominence in recent years as the cause of serious, long-lasting, population-wide health problems.
