Search Results for author: Ada Gavrilovska

Found 5 papers, 2 papers with code

Poster: Making Edge-assisted LiDAR Perceptions Robust to Lossy Point Cloud Compression

no code implementations8 Sep 2023 Jin Heo, Gregorie Phillips, Per-Erik Brodin, Ada Gavrilovska

In this work, we present an interpolation algorithm improving the quality of a LiDAR point cloud to mitigate the perception performance loss due to lossy compression.

3D Object Detection object-detection +1

Flame: Simplifying Topology Extension in Federated Learning

1 code implementation9 May 2023 Harshit Daga, Jaemin Shin, Dhruv Garg, Ada Gavrilovska, Myungjin Lee, Ramana Rao Kompella

We present Flame, a new system that provides flexibility of the topology configuration of distributed FL applications around the specifics of a particular deployment context, and is easily extensible to support new FL architectures.

Federated Learning

Canoe : A System for Collaborative Learning for Neural Nets

no code implementations27 Aug 2021 Harshit Daga, YiWen Chen, Aastha Agrawal, Ada Gavrilovska

For highly distributed environments such as edge computing, collaborative learning approaches eschew the dependence on a global, shared model, in favor of models tailored for each location.

Edge-computing Federated Learning +1

Compiler-Guided Throughput Scheduling for Many-core Machines

no code implementations11 Mar 2021 Girish Mururu, Chao Chen, Chris Porter, Santosh Pande, Ada Gavrilovska

Typical schedulers in multi-tenancy environments make use of reactive, feedback-oriented mechanisms based on performance counters to avoid resource contention but suffer from detection lag and loss of performance.

Distributed, Parallel, and Cluster Computing

Collaboration Versus Cheating

1 code implementation1 Dec 2018 Tony Mason, Ada Gavrilovska, David A. Joyner

We outline how we detected programming plagiarism in an introductory online course for a master's of science in computer science program, how we achieved a statistically significant reduction in programming plagiarism by combining a clear explanation of university and class policy on academic honesty reinforced with a short but formal assessment, and how we evaluated plagiarism rates before SIGand after implementing our policy and assessment.

Computers and Society

Cannot find the paper you are looking for? You can Submit a new open access paper.