research
∙
07/14/2020
A Decentralized Approach to Bayesian Learning
Motivated by decentralized approaches to machine learning, we propose a ...
share
research
∙
03/31/2020
Explaining Motion Relevance for Activity Recognition in Video Deep Learning Models
A small subset of explainability techniques developed initially for imag...
research
∙
11/29/2019
Sanity Checks for Saliency Metrics
Saliency maps are a popular approach to creating post-hoc explanations o...
research
∙
09/18/2019
Wasserstein Distance Based Domain Adaptation for Object Detection
In this paper, we present an adversarial unsupervised domain adaptation ...
research
∙
09/08/2019
Distributed Deep Learning with Event-Triggered Communication
We develop a Distributed Event-Triggered Stochastic GRAdient Descent (DE...
research
∙
04/06/2019
Quickest Event Detection Using Multimodal Data In Nonstationary Environments
Theory and algorithms are developed for event detection using multimodal...
research
∙
04/06/2019
A Bayesian Theory of Change Detection in Statistically Periodic Random Processes
A new class of stochastic processes called independent and periodically ...
research
∙
10/30/2018
Quickest Detection Of Deviations From Periodic Statistical Behavior
A new class of stochastic processes called independent and periodically ...
research
∙
07/02/2018
Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data
A framework is proposed to detect anomalies in multi-modal data. A deep ...
research
∙
03/23/2018
Sequential Event Detection Using Multimodal Data in Nonstationary Environments
The problem of sequential detection of anomalies in multimodal data is c...
research
∙
12/23/2016
