521 citations · 602 across the 8 of their papers we have counts for
9 papers
Residential Electricity Consumption Dataset for Sri Lanka (RECON-SL)
Chanuka Algama, Merl Chandana, Isuruni Fernando +6
This article describes the Residential Electricity Consumption Dataset for Sri Lanka (RECON-SL), a multi-source resource that integrates utility records, high-frequency smart meter…
Decision-Centered Evaluation of Machine Learning Poverty Maps Using Mobile Phone and Satellite Data
Chanuka Algama, Merl Chandana, Viren Dias +1
Identifying the poorest communities is essential for poverty alleviation, but household surveys and censuses are costly and infrequent. Machine learning offers alternative poverty…
Robust Optical Flow Computation: A Higher-Order Differential Approach
Chanuka Algama, Kasun Amarasinghe
In the domain of computer vision, optical flow stands as a cornerstone for unraveling dynamic visual scenes. However, the challenge of accurately estimating optical flow under cond…
Learned Indexes with Distribution Smoothing via Virtual Points
Kasun Amarasinghe, Farhana Choudhury, Jianzhong Qi +1
Recent research on learned indexes has created a new perspective for indexes as models that map keys to their respective storage locations. These learned indexes are created to app…
Preventing Eviction-Caused Homelessness through ML-Informed Distribution of Rental Assistance
Catalina Vajiac, Arun Frey, Joachim Baumann +5
Rental assistance programs provide individuals with financial assistance to prevent housing instabilities caused by evictions and avert homelessness. Since these programs operate u…
On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods
Kasun Amarasinghe, Kit T. Rodolfa, Sérgio Jesus +6
Most existing evaluations of explainable machine learning (ML) methods rely on simplifying assumptions or proxies that do not reflect real-world use cases; the handful of more robu…
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data
Oscar Giles, Kasra Hosseini, Grigorios Mingas +13
Synthetic datasets are often presented as a silver-bullet solution to the problem of privacy-preserving data publishing. However, for many applications, synthetic data has been sho…
Explainable Machine Learning for Public Policy: Use Cases, Gaps, and Research Directions
Kasun Amarasinghe, Kit Rodolfa, Hemank Lamba +1
Explainability is highly-desired in Machine Learning (ML) systems supporting high-stakes policy decisions in areas such as health, criminal justice, education, and employment. Whil…
Building Energy Load Forecasting using Deep Neural Networks
Daniel L. Marino, Kasun Amarasinghe, Milos Manic
Ensuring sustainability demands more efficient energy management with minimized energy wastage. Therefore, the power grid of the future should provide an unprecedented level of fle…