most citedAdaptive Online Sequential ELM for Concept Drift Tackling

21 citations · 69 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG20167 cited

Distributed Averaging CNN-ELM for Big Data

Arif Budiman, Mohamad Ivan Fanany, Chan Basaruddin

Increasing the scalability of machine learning to handle big volume of data is a challenging task. The scale up approach has some limitations. In this paper, we proposed a scale ou…

cs.AI20169 cited

Adaptive Convolutional ELM For Concept Drift Handling in Online Stream Data

Arif Budiman, Mohamad Ivan Fanany, Chan Basaruddin

In big data era, the data continuously generated and its distribution may keep changes overtime. These challenges in online stream of data are known as concept drift. In this paper…

cs.CV201615 cited

Optimization of Convolutional Neural Network using Microcanonical Annealing Algorithm

Vina Ayumi, L. M. Rasdi Rere, Mohamad Ivan Fanany +1

Convolutional neural network (CNN) is one of the most prominent architectures and algorithm in Deep Learning. It shows a remarkable improvement in the recognition and classificatio…

cs.NE20163 cited

Sequence-based Sleep Stage Classification using Conditional Neural Fields

Intan Nurma Yulita, Mohamad Ivan Fanany, Aniati Murni Arymurthy

Sleep signals from a polysomnographic database are sequences in nature. Commonly employed analysis and classification methods, however, ignored this fact and treated the sleep sign…

cs.AI201621 cited

Adaptive Online Sequential ELM for Concept Drift Tackling

Arif Budiman, Mohamad Ivan Fanany, Chan Basaruddin

A machine learning method needs to adapt to over time changes in the environment. Such changes are known as concept drift. In this paper, we propose concept drift tackling method a…

cs.CL2016

A New Data Representation Based on Training Data Characteristics to Extract Drug Named-Entity in Medical Text

Sadikin Mujiono, Mohamad Ivan Fanany, Chan Basaruddin

One essential task in information extraction from the medical corpus is drug name recognition. Compared with text sources come from other domains, the medical text is special and h…