160 citations · 607 across the 73 of their papers we have counts for
8 papers · 1 filter
Training Artificial Neural Networks by Coordinate Search Algorithm
Ehsan Rokhsatyazdi, Shahryar Rahnamayan, Sevil Zanjani Miyandoab +2
Training Artificial Neural Networks poses a challenging and critical problem in machine learning. Despite the effectiveness of gradient-based learning methods, such as Stochastic G…
Monitoring Shortcut Learning using Mutual Information
Mohammed Adnan, Yani Ioannou, Chuan-Yung Tsai +3
The failure of deep neural networks to generalize to out-of-distribution data is a well-known problem and raises concerns about the deployment of trained networks in safety-critica…
Decentralized Federated Learning through Proxy Model Sharing
Shivam Kalra, Junfeng Wen, Jesse C. Cresswell +2
Institutions in highly regulated domains such as finance and healthcare often have restrictive rules around data sharing. Federated learning is a distributed learning framework tha…
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks
Benyamin Ghojogh, Milad Sikaroudi, Sobhan Shafiei +3
Siamese neural network is a very powerful architecture for both feature extraction and metric learning. It usually consists of several networks that share weights. The Siamese conc…
Learning Permutation Invariant Representations using Memory Networks
Shivam Kalra, Mohammed Adnan, Graham Taylor +1
Many real-world tasks such as classification of digital histopathology images and 3D object detection involve learning from a set of instances. In these cases, only a group of inst…
Atrial Fibrillation Detection Using Deep Features and Convolutional Networks
Sara Ross-Howe, H. R. Tizhoosh
Atrial fibrillation is a cardiac arrhythmia that affects an estimated 33.5 million people globally and is the potential cause of 1 in 3 strokes in people over the age of 60. Detect…
Auto-Detection of Safety Issues in Baby Products
Graham Bleaney, Matthew Kuzyk, Julian Man +2
Every year, thousands of people receive consumer product related injuries. Research indicates that online customer reviews can be processed to autonomously identify product safety…
Learning Opposites Using Neural Networks
Shivam Kalra, Aditya Sriram, Shahryar Rahnamayan +1
Many research works have successfully extended algorithms such as evolutionary algorithms, reinforcement agents and neural networks using "opposition-based learning" (OBL). Two typ…