1 citations · 1 across the 5 of their papers we have counts for
5 papers
Accurate and Resource-Efficient Federated Continual Learning
Jebacyril Arockiaraj, Dhruv Parikh, Jayashree Adivarahan +2
Federated continual learning (FCL) must learn from distributed task streams under limited resources, such as communication, computation, memory, and label availability. Existing FC…
ImageHD: Energy-Efficient On-Device Continual Learning of Visual Representations via Hyperdimensional Computing
Jebacyril Arockiaraj, Dhruv Parikh, Viktor Prasanna
On-device continual learning (CL) is critical for edge AI systems operating on non-stationary data streams, but most existing methods rely on backpropagation or exemplar-heavy clas…
System-Level Performance Modeling of Photonic In-Memory Computing
Jebacyril Arockiaraj, Sasindu Wijeratne, Sugeet Sunder +4
Photonic in-memory computing is a high-speed, low-energy alternative to traditional transistor-based digital computing that utilizes high photonic operating frequencies and bandwid…
Primitive-Driven Acceleration of Hyperdimensional Computing for Real-Time Image Classification
Dhruv Parikh, Jebacyril Arockiaraj, Viktor Prasanna
Hyperdimensional Computing (HDC) represents data using extremely high-dimensional, low-precision vectors, termed hypervectors (HVs), and performs learning and inference through lig…
Efficient and Accurate Graph Classification with Hyperdimensional Computing on FPGA
Jebacyril Arockiaraj, Dhruv Parikh, Viktor Prasanna
Real-time, energy-efficient inference on edge devices is essential for graph classification across a range of applications. Hyperdimensional Computing (HDC) is a brain-inspired com…