6 papers
Fiaingen: A financial time series generative method matching real-world data quality
Jože M. Rožanec, Tina Žezlin, Laurentiu Vasiliu +3
Data is vital in enabling machine learning models to advance research and practical applications in finance, where accurate and robust models are essential for investment and tradi…
DQ-Ladder: A Deep Reinforcement Learning-based Bitrate Ladder for Adaptive Video Streaming
Reza Farahani, Zoha Azimi, Vignesh V Menon +4
Adaptive streaming of segmented video over HTTP typically relies on a predefined set of bitrate-resolution pairs, known as a bitrate ladder. However, fixed ladders often overlook v…
ELLMPEG: An Edge-based Agentic LLM Video Processing Tool
Zoha Azimi, Reza Farahani, Radu Prodan +1
Large language models (LLMs), the foundation of generative AI systems like ChatGPT, are transforming many fields and applications, including multimedia, enabling more advanced cont…
Osmotic Learning: A Self-Supervised Paradigm for Decentralized Contextual Data Representation
Mario Colosi, Reza Farahani, Maria Fazio +2
Data within a specific context gains deeper significance beyond its isolated interpretation. In distributed systems, interdependent data sources reveal hidden relationships and lat…
Serverless Everywhere: A Comparative Analysis of WebAssembly Workflows Across Browser, Edge, and Cloud
Mario Colosi, Reza Farahani, Lauri Loven +2
WebAssembly (Wasm) is a binary instruction format that enables portable, sandboxed, and near-native execution across heterogeneous platforms, making it well-suited for serverless w…
Toward Sustainability-Aware LLM Inference on Edge Clusters
Kolichala Rajashekar, Nafiseh Sharghivand, Radu Prodan +1
Large language models (LLMs) require substantial computational resources, leading to significant carbon emissions and operational costs. Although training is energy-intensive, the…