74 citations · 234 across the 37 of their papers we have counts for
16 papers · 1 filter
Focus Session: Hardware and Software Techniques for Accelerating Multimodal Foundation Models
Muhammad Shafique, Abdul Basit, Muhammad Abdullah Hanif +3
This work presents a multi-layered methodology for efficiently accelerating multimodal foundation models (MFMs). It combines hardware and software co-design of transformer blocks w…
ESM: A Framework for Building Effective Surrogate Models for Hardware-Aware Neural Architecture Search
Azaz-Ur-Rehman Nasir, Samroz Ahmad Shoaib, Muhammad Abdullah Hanif +1
Hardware-aware Neural Architecture Search (NAS) is one of the most promising techniques for designing efficient Deep Neural Networks (DNNs) for resource-constrained devices. Surrog…
Democratizing MLLMs in Healthcare: TinyLLaVA-Med for Efficient Healthcare Diagnostics in Resource-Constrained Settings
Aya El Mir, Lukelo Thadei Luoga, Boyuan Chen +2
Deploying Multi-Modal Large Language Models (MLLMs) in healthcare is hindered by their high computational demands and significant memory requirements, which are particularly challe…
Examining Changes in Internal Representations of Continual Learning Models Through Tensor Decomposition
Nishant Suresh Aswani, Amira Guesmi, Muhammad Abdullah Hanif +1
Continual learning (CL) has spurred the development of several methods aimed at consolidating previous knowledge across sequential learning. Yet, the evaluations of these methods h…
Exploring Machine Learning Privacy/Utility trade-off from a hyperparameters Lens
Ayoub Arous, Amira Guesmi, Muhammad Abdullah Hanif +2
Machine Learning (ML) architectures have been applied to several applications that involve sensitive data, where a guarantee of users' data privacy is required. Differentially Priv…
DESCNet: Developing Efficient Scratchpad Memories for Capsule Network Hardware
Alberto Marchisio, Vojtech Mrazek, Muhammad Abdullah Hanif +1
Deep Neural Networks (DNNs) have been established as the state-of-the-art algorithm for advanced machine learning applications. Recently proposed by the Google Brain's team, the Ca…