80 citations · 138 across the 20 of their papers we have counts for
6 papers · 1 filter
Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis
Daniel P. Robinson, Rene Vidal, Chong You
Given an overcomplete dictionary and a signal for some sparse vector whose nonzero entries correspond to linearly independent columns of , classical sparse…
The fastest prox in the west
Benjamín Béjar, Ivan Dokmanić, René Vidal
Proximal operators are of particular interest in optimization problems dealing with non-smooth objectives because in many practical cases they lead to optimization algorithms whose…
On the Regularization Properties of Structured Dropout
Ambar Pal, Connor Lane, René Vidal +1
Dropout and its extensions (eg. DropBlock and DropConnect) are popular heuristics for training neural networks, which have been shown to improve generalization performance in pract…
What is the Largest Sparsity Pattern that Can Be Recovered by 1-Norm Minimization?
Mustafa D. Kaba, Mengnan Zhao, Rene Vidal +2
Much of the existing literature in sparse recovery is concerned with the following question: given a sparsity pattern and a corresponding regularizer, derive conditions on the dict…
Representation Learning on Visual-Symbolic Graphs for Video Understanding
Effrosyni Mavroudi, Benjamín Béjar Haro, René Vidal
Events in natural videos typically arise from spatio-temporal interactions between actors and objects and involve multiple co-occurring activities and object classes. To capture th…
Conformal Symplectic and Relativistic Optimization
Guilherme França, Jeremias Sulam, Daniel P. Robinson +1
Arguably, the two most popular accelerated or momentum-based optimization methods in machine learning are Nesterov's accelerated gradient and Polyaks's heavy ball, both correspondi…