6 citations · 19 across the 9 of their papers we have counts for
11 papers
Kernel Methods and Multi-layer Perceptrons Learn Linear Models in High Dimensions
Mojtaba Sahraee-Ardakan, Melikasadat Emami, Parthe Pandit +2
Empirical observation of high dimensional phenomena, such as the double descent behaviour, has attracted a lot of interest in understanding classical techniques such as kernel meth…
Asymptotics of Ridge Regression in Convolutional Models
Mojtaba Sahraee-Ardakan, Tung Mai, Anup Rao +3
Understanding generalization and estimation error of estimators for simple models such as linear and generalized linear models has attracted a lot of attention recently. This is in…
Implicit Bias of Linear RNNs
Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit +2
Contemporary wisdom based on empirical studies suggests that standard recurrent neural networks (RNNs) do not perform well on tasks requiring long-term memory. However, precise rea…
Generalization Error of Generalized Linear Models in High Dimensions
Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit +2
At the heart of machine learning lies the question of generalizability of learned rules over previously unseen data. While over-parameterized models based on neural networks are no…
Inference in Multi-Layer Networks with Matrix-Valued Unknowns
Parthe Pandit, Mojtaba Sahraee-Ardakan, Sundeep Rangan +2
We consider the problem of inferring the input and hidden variables of a stochastic multi-layer neural network from an observation of the output. The hidden variables in each layer…
Inference with Deep Generative Priors in High Dimensions
Parthe Pandit, Mojtaba Sahraee-Ardakan, Sundeep Rangan +2
Deep generative priors offer powerful models for complex-structured data, such as images, audio, and text. Using these priors in inverse problems typically requires estimating the…
Input-Output Equivalence of Unitary and Contractive RNNs
M. Emami, M. Sahraee-Ardakan, S. Rangan +1
Unitary recurrent neural networks (URNNs) have been proposed as a method to overcome the vanishing and exploding gradient problem in modeling data with long-term dependencies. A ba…
High-Dimensional Bernoulli Autoregressive Process with Long-Range Dependence
Parthe Pandit, Mojtaba Sahraee-Ardakan, Arash A. Amini +2
We consider the problem of estimating the parameters of a multivariate Bernoulli process with auto-regressive feedback in the high-dimensional setting where the number of samples a…
Rigorous Dynamics and Consistent Estimation in Arbitrarily Conditioned Linear Systems
Alyson K. Fletcher, Mojtaba Sahraee-Ardakan, Philip Schniter +1
The problem of estimating a random vector x from noisy linear measurements y = A x + w with unknown parameters on the distributions of x and w, which must also be learned, arises i…
Joint Dictionary Learning for Example-based Image Super-resolution
Mojtaba Sahraee-Ardakan, Mohsen Joneidi
In this paper, we propose a new joint dictionary learning method for example-based image super-resolution (SR), using sparse representation. The low-resolution (LR) dictionary is t…
Expectation Consistent Approximate Inference: Generalizations and Convergence
Alyson K. Fletcher, Mojtaba Sahraee-Ardakan, Sundeep Rangan +1
Approximations of loopy belief propagation, including expectation propagation and approximate message passing, have attracted considerable attention for probabilistic inference pro…