Search Results for author:
Found 9 papers, 7 papers with code
Federated Self-supervised Learning for Video Understanding
The ubiquity of camera-enabled mobile devices has lead to large amounts of unlabelled video data being produced at the edge.
Ranked #1 on
Action Recognition
on UCF-101
(Accuracy metric)
MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation
Medical AI has tremendous potential to advance healthcare by supporting the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving provider and patient experience.
A Channel Coding Benchmark for Meta-Learning
We use our MetaCC benchmark to study several aspects of meta-learning, including the impact of task distribution breadth and shift, which can be controlled in the coding problem.
Predicting Patient Outcomes with Graph Representation Learning
Recent work on predicting patient outcomes in the Intensive Care Unit (ICU) has focused heavily on the physiological time series data, largely ignoring sparse data such as diagnoses and medications.
Single Shot Structured Pruning Before Training
We introduce a method to speed up training by 2x and inference by 3x in deep neural networks using structured pruning applied before training.
Distilling Knowledge from Ensembles of Acoustic Models for Joint CTC-Attention End-to-End Speech Recognition
In the specific context of Automatic Speech Recognition (ASR), distillation from ensembles of acoustic models has recently shown promising results in increasing recognition performance.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Quaternion Neural Networks for Multi-channel Distant Speech Recognition
In this paper, we propose to capture these inter- and intra- structural dependencies with quaternion neural networks, which can jointly process multiple signals as whole quaternion entities.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
The Surprising Behavior Of Graph Neural Networks
We highlight a lack of understanding of the behaviour of Graph Neural Networks (GNNs) in various topological contexts.
Robust Cross-View Gait Recognition with Evidence: A Discriminant Gait GAN (DiGGAN) Approach
Gait as a biometric trait has attracted much attention in many security and privacy applications such as identity recognition and authentication, during the last few decades.
