54 citations · 58 across the 6 of their papers we have counts for
6 papers
SplitLLM: Collaborative Inference of LLMs for Model Placement and Throughput Optimization
Akrit Mudvari, Yuang Jiang, Leandros Tassiulas
Large language models (LLMs) have been a disruptive innovation in recent years, and they play a crucial role in our daily lives due to their ability to understand and generate huma…
Robust and Resource-efficient Machine Learning Aided Viewport Prediction in Virtual Reality
Yuang Jiang, Konstantinos Poularakis, Diego Kiedanski +2
360-degree panoramic videos have gained considerable attention in recent years due to the rapid development of head-mounted displays (HMDs) and panoramic cameras. One major problem…
A Quantitative Theory of Bottleneck Structures for Data Networks
Jordi Ros-Giralt, Noah Amsel, Sruthi Yellamraju +5
The conventional view of the congestion control problem in data networks is based on the principle that a flow's performance is uniquely determined by the state of its bottleneck l…
Diffuser: Efficient Transformers with Multi-hop Attention Diffusion for Long Sequences
Aosong Feng, Irene Li, Yuang Jiang +1
Efficient Transformers have been developed for long sequence modeling, due to their subquadratic memory and time complexity. Sparse Transformer is a popular approach to improving t…
Accelerated Convex Optimization with Stochastic Gradients: Generalizing the Strong-Growth Condition
Víctor Valls, Shiqiang Wang, Yuang Jiang +1
This paper presents a sufficient condition for stochastic gradients not to slow down the convergence of Nesterov's accelerated gradient method. The new condition has the strong-gro…
Model Pruning Enables Efficient Federated Learning on Edge Devices
Yuang Jiang, Shiqiang Wang, Victor Valls +4
Federated learning (FL) allows model training from local data collected by edge/mobile devices while preserving data privacy, which has wide applicability to image and vision appli…