27 citations · 65 across the 11 of their papers we have counts for
12 papers
Adaptive Determinantal Client Scheduling in Federated Learning
Wen Xu, Ben Liang, Gary Boudreau +1
Scheduling clients for model training is critical in federated learning due to both data and system heterogeneity. Most previous works focus on the quality of the scheduled clients…
Adaptive Data Admission and Retention for Streaming Federated Learning
Zhuoyi Zhao, Ben Liang
We study streaming federated learning with limited client memory, where newly generated training data incur time-varying sampling costs and must be selectively admitted and retaine…
Novel Gradient Sparsification Algorithm via Bayesian Inference
Ali Bereyhi, Ben Liang, Gary Boudreau +1
Error accumulation is an essential component of the Top- sparsification method in distributed gradient descent. It implicitly scales the learning rate and prevents the slow-down…
Generative Adversarial Classification Network with Application to Network Traffic Classification
Rozhina Ghanavi, Ben Liang, Ali Tizghadam
Large datasets in machine learning often contain missing data, which necessitates the imputation of missing data values. In this work, we are motivated by network traffic classific…
Beamforming and Device Selection Design in Federated Learning with Over-the-air Aggregation
Faeze Moradi Kalarde, Min Dong, Ben Liang +2
Federated learning (FL) with over-the-air computation can efficiently utilize the communication bandwidth but is susceptible to analog aggregation error. Excluding those devices wi…
Ultra-Low-Complexity Algorithms with Structurally Optimal Multi-Group Multicast Beamforming in Large-Scale Systems
Chong Zhang, Min Dong, Ben Liang
In this work, we propose ultra-low-complexity design solutions for multi-group multicast beamforming in large-scale systems. For the quality-of-service (QoS) problem, by utilizing…
Dynamic Regret of Online Mirror Descent for Relatively Smooth Convex Cost Functions
Nima Eshraghi, Ben Liang
The performance of online convex optimization algorithms in a dynamic environment is often expressed in terms of the dynamic regret, which measures the decision maker's performance…
Online Distributed Coordinated Precoding for Virtualized MIMO Networks with Delayed CSI
Juncheng Wang, Ben Liang, Min Dong +2
We consider online wireless network virtualization (WNV) in a multi-cell multiple-input multiple output (MIMO) system with delayed feedback of channel state information (CSI). Mult…
Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information
Nima Eshraghi, Ben Liang
We consider the problem of distributed online optimization, with a group of learners connected via a dynamic communication graph. The goal of the learners is to track the global mi…
Gradient and Projection Free Distributed Online Min-Max Resource Optimization
Jingrong Wang, Ben Liang
We consider distributed online min-max resource allocation with a set of parallel agents and a parameter server. Our goal is to minimize the pointwise maximum over a set of time-va…
On the Generalization of Stochastic Gradient Descent with Momentum
Ali Ramezani-Kebrya, Ashish Khisti, Ben Liang
While momentum-based methods, in conjunction with stochastic gradient descent (SGD), are widely used when training machine learning models, there is little theoretical understandin…
On the Generalization of Stochastic Gradient Descent with Momentum
Ali Ramezani-Kebrya, Kimon Antonakopoulos, Volkan Cevher +2
While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on t…