Search Results for author: Arash A. Amini

Found 23 papers, 9 papers with code

Step and Smooth Decompositions as Topological Clustering

no code implementations9 Nov 2023 Luciano Vinas, Arash A. Amini

Alternately, the problem can be viewed as clustering in the presence of structured (smooth) contaminant.


Simplifying GNN Performance with Low Rank Kernel Models

1 code implementation8 Oct 2023 Luciano Vinas, Arash A. Amini

We posit that many of the current GNN architectures may be over-engineered.

Node Classification

Nested stochastic block model for simultaneously clustering networks and nodes

no code implementations18 Jul 2023 Nathaniel Josephs, Arash A. Amini, Marina Paez, Lizhen Lin

We introduce the nested stochastic block model (NSBM) to cluster a collection of networks while simultaneously detecting communities within each network.

Clustering Stochastic Block Model

LapGM: A Multisequence MR Bias Correction and Normalization Model

1 code implementation27 Sep 2022 Luciano Vinas, Arash A. Amini, Jade Fischer, Atchar Sudhyadhom

A spatially regularized Gaussian mixture model, LapGM, is proposed for the bias field correction and magnetic resonance normalization problem.

Target alignment in truncated kernel ridge regression

no code implementations28 Jun 2022 Arash A. Amini, Richard Baumgartner, Dai Feng

We show that for polynomial alignment, there is an \emph{over-aligned} regime, in which TKRR can achieve a faster rate than what is achievable by full KRR.


A non-graphical representation of conditional independence via the neighbourhood lattice

no code implementations12 Jun 2022 Arash A. Amini, Bryon Aragam, Qing Zhou

We introduce and study the neighbourhood lattice decomposition of a distribution, which is a compact, non-graphical representation of conditional independence that is valid in the absence of a faithful graphical representation.


Distributed Learning of Generalized Linear Causal Networks

no code implementations23 Jan 2022 Qiaoling Ye, Arash A. Amini, Qing Zhou

We consider the task of learning causal structures from data stored on multiple machines, and propose a novel structure learning method called distributed annealing on regularized likelihood score (DARLS) to solve this problem.

Distributed Optimization

Adjusted chi-square test for degree-corrected block models

1 code implementation30 Dec 2020 Linfan Zhang, Arash A. Amini

When applied sequentially, the test can also be used to determine the number of communities.


Concentration of kernel matrices with application to kernel spectral clustering

no code implementations7 Sep 2019 Arash A. Amini, Zahra S. Razaee

We derive nonasymptotic exponential concentration inequalities for Lipschitz kernels assuming that the data points are independent draws from a class of multivariate distributions on $\mathbb R^d$, including the strongly log-concave distributions under affine transformations.


On perfectness in Gaussian graphical models

no code implementations3 Sep 2019 Arash A. Amini, Bryon Aragam, Qing Zhou

Knowing when a graphical model is perfect to a distribution is essential in order to relate separation in the graph to conditional independence in the distribution, and this is particularly important when performing inference from data.

Spectrally-truncated kernel ridge regression and its free lunch

no code implementations14 Jun 2019 Arash A. Amini

We show that, as long as the RKHS is infinite-dimensional, there is a threshold on $r$, above which, the spectrally-truncated KRR surprisingly outperforms the full KRR in terms of the minimax risk, where the minimum is taken over the regularization parameter.


Optimizing regularized Cholesky score for order-based learning of Bayesian networks

1 code implementation28 Apr 2019 Qiaoling Ye, Arash A. Amini, Qing Zhou

We propose a novel structure learning method, annealing on regularized Cholesky score (ARCS), to search over topological sorts, or permutations of nodes, for a high-scoring Bayesian network.

Hierarchical Stochastic Block Model for Community Detection in Multiplex Networks

1 code implementation30 Mar 2019 Arash A. Amini, Marina S. Paez, Lizhen Lin

Moreover, our model automatically picks up the necessary number of communities at each layer (as validated by real data examples).

Community Detection Stochastic Block Model

Exact slice sampler for Hierarchical Dirichlet Processes

2 code implementations21 Mar 2019 Arash A. Amini, Marina Paez, Lizhen Lin, Zahra S. Razaee

We propose an exact slice sampler for Hierarchical Dirichlet process (HDP) and its associated mixture models (Teh et al., 2006).

High-Dimensional Bernoulli Autoregressive Process with Long-Range Dependence

no code implementations19 Mar 2019 Parthe Pandit, Mojtaba Sahraee-Ardakan, Arash A. Amini, Sundeep Rangan, Alyson K. Fletcher

We derive precise upper bounds on the mean-squared estimation error in terms of the number of samples, dimensions of the process, the lag $p$ and other key statistical properties of the model.

Gaussian Processes Vocal Bursts Intensity Prediction

Optimal Bipartite Network Clustering

no code implementations15 Mar 2018 Zhixin Zhou, Arash A. Amini

The provable algorithm is derived from a general class of pseudo-likelihood biclustering algorithms that employ simple EM type updates.

Clustering Community Detection +1

Analysis of spectral clustering algorithms for community detection: the general bipartite setting

no code implementations12 Mar 2018 Zhixin Zhou, Arash A. Amini

We consider spectral clustering algorithms for community detection under a general bipartite stochastic block model (SBM).

Clustering Community Detection +1

The neighborhood lattice for encoding partial correlations in a Hilbert space

1 code implementation3 Nov 2017 Arash A. Amini, Bryon Aragam, Qing Zhou

We study the computational complexity of computing these structures and show that under a sparsity assumption, they can be computed in polynomial time, even in the absence of the assumption of perfectness to a graph.

Dimensionality Reduction regression

Matched bipartite block model with covariates

no code implementations15 Mar 2017 Zahra S. Razaee, Arash A. Amini, Jingyi Jessica Li

Community detection or clustering is a fundamental task in the analysis of network data.

Clustering Community Detection +1

Learning Directed Acyclic Graphs with Penalized Neighbourhood Regression

1 code implementation29 Nov 2015 Bryon Aragam, Arash A. Amini, Qing Zhou

We study a family of regularized score-based estimators for learning the structure of a directed acyclic graph (DAG) for a multivariate normal distribution from high-dimensional data with $p\gg n$.


On semidefinite relaxations for the block model

1 code implementation21 Jun 2014 Arash A. Amini, Elizaveta Levina

We put ours and previously proposed SDPs in a unified framework, as relaxations of the MLE over various sub-classes of the SBM, revealing a connection to sparse PCA.

Community Detection Graphon Estimation +1

Bayesian inference as iterated random functions with applications to sequential inference in graphical models

no code implementations NeurIPS 2013 Arash A. Amini, XuanLong Nguyen

We propose a general formalism of iterated random functions with semigroup property, under which exact and approximate Bayesian posterior updates can be viewed as specific instances.

Bayesian Inference Change Point Detection

Pseudo-likelihood methods for community detection in large sparse networks

no code implementations10 Jul 2012 Arash A. Amini, Aiyou Chen, Peter J. Bickel, Elizaveta Levina

Many algorithms have been proposed for fitting network models with communities, but most of them do not scale well to large networks, and often fail on sparse networks.

Clustering Community Detection +1

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