1 citations · 1 across the 7 of their papers we have counts for
8 papers
Rank-Adaptive Matrix-Free Atomic Quantum State Tomography
Amirhossein Taherpour, Alireza Sadeghi, Georgios B. Giannakis
Quantum state tomography estimates an unknown density operator from measurement data. Dense reconstruction however, can be impractical for many-qubit systems because the Hilbert-sp…
Low-Rank Adaptation Redux for Large Models
Bingcong Li, Yilang Zhang, Georgios B. Giannakis
Low-rank adaptation (LoRA) has emerged as the de facto standard for parameter-efficient fine-tuning (PEFT) of foundation models, enabling the adaptation of billion-parameter networ…
Distributed Learning of Quantum State Tomography Robust to Readout Errors
Amirhossein Taherpour, Alireza Sadeghi, Georgios B. Giannakis
Scalable estimation of quantum states with readout errors is a central challenge in large multiqubit systems. Existing overlapping-tomography methods improve scalability by working…
Binomial Gradient-Based Meta-Learning for Enhanced Meta-Gradient Estimation
Yilang Zhang, Abraham Jaeger Mountain, Bingcong Li +1
Meta-learning offers a principled framework leveraging \emph{task-invariant} priors from related tasks, with which \emph{task-specific} models can be fine-tuned on downstream tasks…
Conformalized Gaussian processes for online uncertainty quantification over graphs
Jinwen Xu, Qin Lu, Georgios B. Giannakis
Uncertainty quantification (UQ) over graphs arises in a number of safety-critical applications in network science. The Gaussian process (GP), as a classical Bayesian framework for…
BOSfM: A View Planning Framework for Optimal 3D Reconstruction of Agricultural Scenes
Athanasios Bacharis, Konstantinos D. Polyzos, Georgios B. Giannakis +1
Active vision (AV) has been in the spotlight of robotics research due to its emergence in numerous applications including agricultural tasks such as precision crop monitoring and a…
Deploying AI for Signal Processing education: Selected challenges and intriguing opportunities
Jarvis Haupt, Qin Lu, Yanning Shen +5
Powerful artificial intelligence (AI) tools that have emerged in recent years -- including large language models, automated coding assistants, and advanced image and speech generat…
Online scalable Gaussian processes with conformal prediction for guaranteed coverage
Jinwen Xu, Qin Lu, Georgios B. Giannakis
The Gaussian process (GP) is a Bayesian nonparametric paradigm that is widely adopted for uncertainty quantification (UQ) in a number of safety-critical applications, including rob…