15 citations · 27 across the 8 of their papers we have counts for
13 papers
A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality
Xuhui Zhang, Jose Blanchet, Soumyadip Ghosh +1
We study the problem of transfer learning, observing that previous efforts to understand its information-theoretic limits do not fully exploit the geometric structure of the source…
Quantum Topological Data Analysis with Linear Depth and Exponential Speedup
Shashanka Ubaru, Ismail Yunus Akhalwaya, Mark S. Squillante +2
Quantum computing offers the potential of exponential speedups for certain classical computations. Over the last decade, many quantum machine learning (QML) algorithms have been pr…
Solving sparse linear systems with approximate inverse preconditioners on analog devices
Vasileios Kalantzis, Anshul Gupta, Lior Horesh +3
Sparse linear system solvers are computationally expensive kernels that lie at the heart of numerous applications. This paper proposes a flexible preconditioning framework to subst…
Unbiased Gradient Estimation for Distributionally Robust Learning
Soumyadip Ghosh, Mark Squillante
Seeking to improve model generalization, we consider a new approach based on distributionally robust learning (DRL) that applies stochastic gradient descent to the outer minimizati…
Optimal Scheduling Control in Fluid Models of General Input-Queued Switches
Yingdong Lu, Mark S. Squillante, Tonghoon Suk
Most of the early input-queued switch research focused on establishing throughput optimality of the max-weight scheduling policy, with some recent research showing that max-weight…
On Heavy-Traffic Optimal Scaling of -Weighted MaxWeight Scheduling in Input-Queued Switches
Yingdong Lu, Siva Theja Maguluri, Mark S. Squillante +1
We consider the optimal control of input-queued switches under a cost-weighted variant of MaxWeight scheduling, for which we establish theoretical properties that include showing t…