research
∙
03/21/2023
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection
Federated Learning (FL) has been gaining popularity as a collaborative l...
share
research
∙
01/15/2023
EENet: Learning to Early Exit for Adaptive Inference
Budgeted adaptive inference with early exits is an emerging technique to...
research
∙
02/01/2021
Spatio-temporal Weather Forecasting and Attention Mechanism on Convolutional LSTMs
Numerical weather forecasting on high-resolution physical models consume...
research
∙
06/17/2020
Markovian RNN: An Adaptive Time Series Prediction Network with HMM-based Switching for Nonstationary Environments
We investigate nonlinear regression for nonstationary sequential data. I...
research
∙
05/25/2020
Unsupervised Online Anomaly Detection On Irregularly Sampled Or Missing Valued Time-Series Data Using LSTM Networks
We study anomaly detection and introduce an algorithm that processes var...
research
∙
05/16/2020
Achieving Online Regression Performance of LSTMs with Simple RNNs
Recurrent Neural Networks (RNNs) are widely used for online regression d...
research
∙
03/07/2020
Modeling of Spatio-Temporal Hawkes Processes with Randomized Kernels
We investigate spatio-temporal event analysis using point processes. Inf...
research
∙
03/07/2020