72 citations · 542 across the 65 of their papers we have counts for
4 papers · 1 filter
Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat
David A. Quiroga, Anastasios Kyrillidis
We propose a non-convex optimization algorithm, based on the Burer-Monteiro (BM) factorization, for the quantum process tomography problem, in order to estimate a low-rank process…
Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty
Carlos Quintero-Peña, Wil Thomason, Zachary Kingston +2
Motion planning under sensing uncertainty is critical for robots in unstructured environments to guarantee safety for both the robot and any nearby humans. Most work on planning un…
Fast FixMatch: Faster Semi-Supervised Learning with Curriculum Batch Size
John Chen, Chen Dun, Anastasios Kyrillidis
Advances in Semi-Supervised Learning (SSL) have almost entirely closed the gap between SSL and Supervised Learning at a fraction of the number of labels. However, recent performanc…
Provable Accelerated Convergence of Nesterov's Momentum for Deep ReLU Neural Networks
Fangshuo Liao, Anastasios Kyrillidis
Current state-of-the-art analyses on the convergence of gradient descent for training neural networks focus on characterizing properties of the loss landscape, such as the Polyak-L…