6 papers
One-Bit Quantization for Random Features Models
Danil Akhtiamov, Reza Ghane, Babak Hassibi
Recent advances in neural networks have led to significant computational and memory demands, spurring interest in one-bit weight compression to enable efficient inference on resour…
A Precise Performance Analysis of the Randomized Singular Value Decomposition
Danil Akhtiamov, Reza Ghane, Babak Hassibi
The Randomized Singular Value Decomposition (RSVD) is a widely used algorithm for efficiently computing low-rank approximations of large matrices, without the need to construct a f…
Beyond Quadratic Costs: A Bregman Divergence Approach to H Control
Joudi Hajar, Reza Ghane, Babak Hassibi
In the past couple of decades, non-quadratic convex penalties have reshaped signal processing and machine learning; in robust control, however, general convex costs break the Ricca…
Beyond Quadratic Costs in LQR: Bregman Divergence Control
Babak Hassibi, Joudi Hajar, Reza Ghane
In the past couple of decades, the use of ``non-quadratic" convex cost functions has revolutionized signal processing, machine learning, and statistics, allowing one to customize s…
Robust Mean Estimation With Auxiliary Samples
Barron Han, Danil Akhtiamov, Reza Ghane +1
In data-driven learning and inference tasks, the high cost of acquiring samples from the target distribution often limits performance. A common strategy to mitigate this challenge…
Gaussian Universality for Diffusion Models
Reza Ghane, Anthony Bao, Danil Akhtiamov +1
We investigate Gaussian Universality for data distributions generated via diffusion models. By Gaussian Universality we mean that the test error of a generalized linear model $f(\m…