6 papers
Communication-Aware Model Distributed Inference via Latent Representation Compression
Peyman Gholami, Theodoros-Thirimachos Davarakis, Teng Li +9
We study optimization of distributed model inference over resource-constrained edge resources. We propose a framework that optimizes the trade-off between model accuracy and commun…
A Tale of Two Learning Algorithms: Multiple Stream Random Walk and Asynchronous Gossip
Peyman Gholami, Hulya Seferoglu
Although gossip and random walk-based learning algorithms are widely known for decentralized learning, there has been limited theoretical and experimental analysis to understand th…
Streamlining Image Editing with Layered Diffusion Brushes
Peyman Gholami, Robert Xiao
Denoising diffusion models have emerged as powerful tools for image manipulation, yet interactive, localized editing workflows remain underdeveloped. We introduce Layered Diffusion…
Differentiated Aggregation to Improve Generalization in Federated Learning
Peyman Gholami, Hulya Seferoglu
This paper focuses on reducing the communication cost of federated learning by exploring generalization bounds and representation learning. We first characterize a tighter generali…
DIGEST: Fast and Communication Efficient Decentralized Learning with Local Updates
Peyman Gholami, Hulya Seferoglu
Two widely considered decentralized learning algorithms are Gossip and random walk-based learning. Gossip algorithms (both synchronous and asynchronous versions) suffer from high c…
AutoDepthNet: High Frame Rate Depth Map Reconstruction using Commodity Depth and RGB Cameras
Peyman Gholami, Robert Xiao
Depth cameras have found applications in diverse fields, such as computer vision, artificial intelligence, and video gaming. However, the high latency and low frame rate of existin…