6 accepted papers
Federated Learning (FL) is a privacy-preserving algorithm that enables multiple clients to collaboratively train a global model without sharing their local data. This learning algorithm is particularly valuable in privacy-sensitive applications such as Human Activity Recognition (HAR), where users a…
Despite the recent advancements in information retrieval (IR), zero-shot IR remains a significant challenge, especially when dealing with new domains, languages, and newly-released use cases that lack historical query traffic from existing users. For such cases, it is common to use query augmentatio…
Electroencephalography (EEG) based emotion recognition is gaining substantial interest because of its strong association with the area of brain-computer interface. Even though several works exist in the literature, it is still challenging to find discriminative features that can generalize well to d…
The size of embeddings generated by large language models can negatively affect system latency and model size in certain downstream practical applications (e.g. KNN search). In this work, we propose EmbedTextNet, a light add-on network that can be appended to an arbitrary language model to generate…
Post-traumatic stress disorder is a major public health concern with a lifetime prevalence rate of 6.1-9.2% in North America. PTSD is known to alter the autonomic nervous system leading to chronic sympathetic arousal including heightened anxiety and hypervigilance. Pupillometry offers a quick and ac…
This paper investigates the employment of photoplethysmography (PPG) for user authentication systems. Time-stable and user-specific features are developed by stretching the signal, designing a convolutional neural network and performing a variation-stable approach with three score fusions. Two evalu…