62 citations · 76 across the 13 of their papers we have counts for
14 papers
Online Learning for Multi-Layer Hierarchical Inference under Partial and Policy-Dependent Feedback
Haoran Zhang, Seohyeon Cha, Hasan Burhan Beytur +3
Hierarchical inference systems route tasks across multiple computational layers, where each node may either finalize a prediction locally or offload the task to a node in the next…
Batching-Aware Joint Model Onloading and Offloading for Hierarchical Multi-Task Inference
Seohyeon Cha, Kevin Chan, Gustavo de Veciana +1
The growing demand for intelligent services on resource-constrained edge devices has spurred the development of collaborative inference systems that distribute workloads across end…
Fundamentals of Caching Layered Data objects
Agrim Bari, Gustavo de Veciana, George Kesidis
The effective management of large amounts of data processed or required by today's cloud or edge computing systems remains a fundamental challenge. This paper focuses on cache mana…
Generative Diffusion Model-based Compression of MIMO CSI
Heasung Kim, Taekyun Lee, Hyeji Kim +6
While neural lossy compression techniques have markedly advanced the efficiency of Channel State Information (CSI) compression and reconstruction for feedback in MIMO communication…
Network Adaptive Federated Learning: Congestion and Lossy Compression
Parikshit Hegde, Gustavo de Veciana, Aryan Mokhtari
In order to achieve the dual goals of privacy and learning across distributed data, Federated Learning (FL) systems rely on frequent exchanges of large files (model updates) betwee…
Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints
Monica Ribero, Haris Vikalo, Gustavo De Veciana
Federated learning systems facilitate training of global models in settings where potentially heterogeneous data is distributed across a large number of clients. Such systems opera…
Performance Analysis of RSU-based Multihomed Multilane Vehicular Networks
Saadallah Kassir, Pablo Caballero, Gustavo de Veciana +3
Motivated by the potentially high downlink traffic demands of commuters in future autonomous vehicles, we study a network architecture where vehicles use Vehicle-to-Vehicle (V2V) l…
Constrained Network Slicing Games: Achieving service guarantees and network efficiency
Jiaxiao Zheng, Gustavo de Veciana, Albert Banchs
Network slicing is a key capability for next generation mobile networks. It enables one to cost effectively customize logical networks over a shared infrastructure. A critical comp…
Performance-Complexity Tradeoffs in Greedy Weak Submodular Maximization with Random Sampling
Abolfazl Hashemi, Haris Vikalo, Gustavo de Veciana
Many problems in signal processing and machine learning can be formalized as weak submodular optimization tasks. For such problems, a simple greedy algorithm (\textsc{Greedy}) is g…
Modeling and Optimization of Human-machine Interaction Processes via the Maximum Entropy Principle
Jiaxiao Zheng, Gustavo de Veciana
We propose a data-driven framework to enable the modeling and optimization of human-machine interaction processes, e.g., systems aimed at assisting humans in decision-making or lea…
Modeling and Analysis of Data Harvesting Architecture based on Unmanned Aerial Vehicles
Chang-sik Choi, Francois Baccelli, Gustavo de Veciana
This paper explores an emerging wireless Internet-of-things (IoT) architecture based on unmanned aerial vehicles (UAVs). We consider a network where a fleet of UAVs at a fixed alti…
Elastic Multi-resource Network Slicing: Can Protection Lead to Improved Performance?
Jiaxiao Zheng, Gustavo de Veciana
In order to meet the performance/privacy requirements of future data-intensive mobile applications, e.g., self-driving cars, mobile data analytics, and AR/VR, service providers are…
Performance and Scaling of Collaborative Sensing and Networking for Automated Driving Applications
Yicong Wang, Gustavo de Veciana, Takayuki Shimizu +1
A critical requirement for automated driving systems is enabling situational awareness in dynamically changing environments. To that end vehicles will be equipped with diverse sens…
Poly-Symmetry in Processor-Sharing Systems
Thomas Bonald, Céline Comte, Virag Shah +1
We consider a system of processor-sharing queues with state-dependent service rates. These are allocated according to balanced fairness within a polymatroid capacity set. Balanced…