341 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Institut Polytechnique de ParisFR3 papers
- Los Alamos National LaboratoryUS3 papers
- Télécom SudParisFR3 papers
- ARM (United Kingdom)GB2 papers
- Intel (United Kingdom)GB2 papers
- Stanford UniversityUS2 papers
- Stony Brook UniversityUS2 papers
- The University of Texas at AustinUS2 papers
- Universitat Politècnica de CatalunyaES2 papers
- University of California San DiegoUS2 papers
- University of CambridgeGB2 papers
- University of RochesterUS2 papers
8 papers · 1 filter
Federated Learning Based on Dynamic Regularization
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro +3
We propose a novel federated learning method for distributively training neural network models, where the server orchestrates cooperation between a subset of randomly chosen device…
UCX Programming Interface for Remote Function Injection and Invocation
Luis E. Peña, Wenbin Lu, Pavel Shamis +1
Network library APIs have historically been developed with the emphasis on data movement, placement, and communication semantics. Many communication semantics are available across…
Two-Chains: High Performance Framework for Function Injection and Execution
Megan Grodowitz, Luis E. Peña, Curtis Dunham +3
Some important problems, such as semantic graph analysis, require large-scale irregular applications composed of many coordinating tasks that operate on a shared data set so big it…
A Fokker-Planck Solver to Model MTJ Stochasticity
Fernando García-Redondo, Pranay Prabhat, Mudit Bhargava
Magnetic Tunnel Junctions (MTJs) constitute the novel memory element in STT-MRAM, which is ramping to production at major foundries as an eFlash replacement. MTJ switching exhibits…
Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs
Lorena Qendro, Sangwon Ha, René de Jong +1
Quantized neural networks (NN) are the common standard to efficiently deploy deep learning models on tiny hardware platforms. However, we notice that quantized NNs are as vulnerabl…
Active multi-fidelity Bayesian online changepoint detection
Gregory W. Gundersen, Diana Cai, Chuteng Zhou +2
Online algorithms for detecting changepoints, or abrupt shifts in the behavior of a time series, are often deployed with limited resources, e.g., to edge computing settings such as…
On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks
Martin Ferianc, Partha Maji, Matthew Mattina +1
Bayesian neural networks (BNNs) are making significant progress in many research areas where decision-making needs to be accompanied by uncertainty estimation. Being able to quanti…
Virtual-Link: A Scalable Multi-Producer, Multi-Consumer Message Queue Architecture for Cross-Core Communication
Qinzhe Wu, Jonathan Beard, Ashen Ekanayake +2
Cross-core communication is increasingly a bottleneck as the number of processing elements increase per system-on-chip. Typical hardware solutions to cross-core communication are o…