3 papers
cs.LG2026
INAR-VL: Input-Aware Routing for Edge-Cloud Vision-Language Inference
Ahmed Å abanoviÄ, Paul Joe Maliakel, Ivona BrandiÄ
Edge deployment of Vision-Language Models (VLMs) faces a tradeoff between latency and accuracy: cloud execution provides high-quality predictions but incurs communication delay and…
cs.LG2026
Characterizing LLM Inference Energy-Performance Tradeoffs across Workloads and GPU Scaling
Paul Joe Maliakel, Shashikant Ilager, Ivona Brandic
LLM inference exhibits substantial variability across queries and execution phases, yet inference configurations are often applied uniformly. We present a measurement-driven charac…
cs.LG2024
FLIGAN: Enhancing Federated Learning with Incomplete Data using GAN
Paul Joe Maliakel, Shashikant Ilager, Ivona Brandic
Federated Learning (FL) provides a privacy-preserving mechanism for distributed training of machine learning models on networked devices (e.g., mobile devices, IoT edge nodes). It…