We show a hardness result for random smoothing to achieve certified
adve...
We consider universal adversarial patches for faces - small visual eleme...
We study the low rank approximation problem of any given matrix A over
R...
We provide efficient algorithms for overconstrained linear regression
pr...
We identify a trade-off between robustness and accuracy that serves as a...
We study the problem of alleviating the instability issue in the GAN tra...
We consider the tensor completion problem of predicting the missing entr...
We show that for the problem of testing if a matrix A ∈ F^n × n
has rank...
Several recently proposed architectures of neural networks such as ResNe...
In the problem of adaptive compressed sensing, one wants to estimate an
...
We show that the (stochastic) gradient descent algorithm provides an imp...
We study the problem of recovering a low-rank matrix X^ from linear
meas...
A Distance Labeling scheme is a data structure that can answer shortest...
Tomal et al. (2015) introduced the notion of "phalanxes" in the context ...
We study the strong duality of non-convex matrix factorization: we show ...
We study the problem of interactively learning a binary classifier using...
We provide new results concerning noise-tolerant and sample-efficient
le...
Subspace recovery from corrupted and missing data is crucial for various...
Rank minimization has attracted a lot of attention due to its robustness...