3 citations · 6 across the 7 of their papers we have counts for
7 papers
Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment
Nathanaël Haas, François Gatine, Augustin M Cosse +1
Understanding why gradient-based training in deep networks exhibits strong implicit bias remains challenging, in part because tractable singular-value dynamics are typically availa…
Infinite families of graphs and stable completion of arbitrary matrices, Part I
Augustin Cosse
We study deterministic constructions of graphs for which the unique completion of low rank matrices is generically possible regardless of the values of the entries. We relate the c…
Sparse recovery from quadratic equations, part II: hardness and incoherence
Augustin Cosse
We study the square root bottleneck in the recovery of sparse vectors from quadratic equations. It is acknowledged that a sparse vector , $\| \mathbf…
In the recovery of sparse vectors from quadratic measurements, the presence of linear terms breaks the square root bottleneck
Augustin Cosse
Motivated by recent results in the statistical physics of spin glasses, we study the recovery of a sparse vector , $\|\mathbf{x}_0\|_{\ell_0} = k<…
Compressed Super-Resolution I: Maximal Rank Sum-of-Squares
Augustin Cosse
Let denote an -atomic measure defined on , satisfying . Let $η(θ) = \sum_{τ\in S} a_τD_n(θ-…
Stable rank one matrix completion is solved by two rounds of semidefinite programming relaxation
Augustin Cosse, Laurent Demanet
This paper studies the problem of deterministic rank-one matrix completion. It is known that the simplest semidefinite programming relaxation, involving minimization of the nuclear…
From Blind deconvolution to Blind Super-Resolution through convex programming
Augustin Cosse
This paper discusses the recovery of an unknown signal through the result of its convolution with an unknown filter . This problem, also kno…