Search Results for author: Amin Jalali

Found 10 papers, 0 papers with code

Evaluating Perceived Usefulness and Ease of Use of CMMN and DCR

no code implementations20 Mar 2021 Amin Jalali

The study is performed by educating master level students with these languages over eight weeks by giving feedback on their assignments to reduce perceptions biases.

Persistent Reductions in Regularized Loss Minimization for Variable Selection

no code implementations30 Nov 2020 Amin Jalali

In the context of regularized loss minimization with polyhedral gauges, we show that for a broad class of loss functions (possibly non-smooth and non-convex) and under a simple geometric condition on the input data it is possible to efficiently identify a subset of features which are guaranteed to have zero coefficients in all optimal solutions in all problems with loss functions from said class, before any iterative optimization has been performed for the original problem.

Variable Selection

2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs

no code implementations19 Feb 2019 Amirhossein Taghvaei, Amin Jalali

We provide a framework to approximate the 2-Wasserstein distance and the optimal transport map, amenable to efficient training as well as statistical and geometric analysis.

Missing Data in Sparse Transition Matrix Estimation for Sub-Gaussian Vector Autoregressive Processes

no code implementations26 Feb 2018 Amin Jalali, Rebecca Willett

In such a scenario, where covariates are highly interdependent and partially missing, new theoretical challenges arise.

Time Series

Subspace Clustering via Tangent Cones

no code implementations NeurIPS 2017 Amin Jalali, Rebecca Willett

Given samples lying on any of a number of subspaces, subspace clustering is the task of grouping the samples based on the their corresponding subspaces.

Graph Clustering

Subspace Clustering with Missing and Corrupted Data

no code implementations8 Jul 2017 Zachary Charles, Amin Jalali, Rebecca Willett

Given full or partial information about a collection of points that lie close to a union of several subspaces, subspace clustering refers to the process of clustering the points according to their subspace and identifying the subspaces.

Relative Density and Exact Recovery in Heterogeneous Stochastic Block Models

no code implementations15 Dec 2015 Amin Jalali, Qiyang Han, Ioana Dumitriu, Maryam Fazel

For instance, $\log n$ is considered to be the standard lower bound on the cluster size for exact recovery via convex methods, for homogenous SBM.

Stochastic Block Model

Variational Gram Functions: Convex Analysis and Optimization

no code implementations16 Jul 2015 Amin Jalali, Maryam Fazel, Lin Xiao

We propose a new class of convex penalty functions, called \emph{variational Gram functions} (VGFs), that can promote pairwise relations, such as orthogonality, among a set of vectors in a vector space.

General Classification

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