Search Results for author: Md. Rakibul Islam

Found 6 papers, 3 papers with code

An Empirical Study of the Relationships between Code Readability and Software Complexity

no code implementations30 Aug 2019 Duaa Alawad, Manisha Panta, Minhaz Zibran, Md. Rakibul Islam

Code readability and software complexity are important software quality metrics that impact other software metrics such as maintainability, reusability, portability and reliability.

BIG-bench Machine Learning

Effectiveness of Tree-based Ensembles for Anomaly Discovery: Insights, Batch and Streaming Active Learning

2 code implementations23 Jan 2019 Shubhomoy Das, Md. Rakibul Islam, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa

Our results show that active learning allows us to discover significantly more anomalies than state-of-the-art unsupervised baselines, our batch active learning algorithm discovers diverse anomalies, and our algorithms under the streaming-data setup are competitive with the batch setup.

Active Learning Anomaly Detection +1

GLAD: GLocalized Anomaly Detection via Human-in-the-Loop Learning

2 code implementations2 Oct 2018 Md. Rakibul Islam, Shubhomoy Das, Janardhan Rao Doppa, Sriraam Natarajan

Human analysts that use anomaly detection systems in practice want to retain the use of simple and explainable global anomaly detectors.

Anomaly Detection

Active Anomaly Detection via Ensembles

2 code implementations17 Sep 2018 Shubhomoy Das, Md. Rakibul Islam, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa

First, we present an important insight into how anomaly detector ensembles are naturally suited for active learning.

Active Learning Anomaly Detection +1

Preference-Guided Planning: An Active Elicitation Approach

no code implementations19 Apr 2018 Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao, Doppa, Dan Roth, Sriraam Natarajan

Planning with preferences has been employed extensively to quickly generate high-quality plans.

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