High-dimensional analysis of semidefinite relaxations for sparse principal components. - Arash A. Amini; Martin J. Wainwright (ISIT, 2008)

Message-passing sequential detection of multiple change points in networks. - XuanLong Nguyen; Arash A. Amini; Ram Rajagopal (ISIT, 2012)

Fitting community models to large sparse networks - Aiyou Chen; Arash A. Amini; Peter J. Bickel; Elizaveta Levina (CoRR, 2012)

Approximation properties of certain operator-induced norms on Hilbert spaces. - Arash A. Amini; Martin J. Wainwright (J. Approx. Theory, 2012)

Bayesian inference as iterated random functions with applications to sequential inference in graphical models. - Arash A. Amini; XuanLong Nguyen (NIPS, 2013)

Sequential Detection of Multiple Change Points in Networks: A Graphical Model Approach. - Arash A. Amini; XuanLong Nguyen (IEEE Trans. Inf. Theory, 2013)

On semidefinite relaxations for the block model. - Arash A. Amini; Elizaveta Levina (CoRR, 2014)

Learning Directed Acyclic Graphs with Penalized Neighbourhood Regression. - Bryon Aragam; Arash A. Amini; Qing Zhou (CoRR, 2015)

Variable Importance Using Decision Trees. - S. Jalil Kazemitabar; Arash A. Amini; Adam E. Bloniarz; Ameet Talwalkar (NIPS, 2017)

Partial correlation graphs and the neighborhood lattice. - Arash A. Amini; Bryon Aragam; Qing Zhou (CoRR, 2017)

Sparse Multivariate Bernoulli Processes in High Dimensions. - Parthe Pandit; Mojtaba Sahraee-Ardakan; Arash A. Amini; Sundeep Rangan; Alyson K. Fletcher (AISTATS, 2019)

Globally optimal score-based learning of directed acyclic graphs in high-dimensions. - Bryon Aragam; Arash A. Amini; Qing Zhou (NeurIPS, 2019)

Exact slice sampler for Hierarchical Dirichlet Processes. - Arash A. Amini; Marina S. Paez; Lizhen Lin; Zahra S. Razaee (CoRR, 2019)

High-Dimensional Bernoulli Autoregressive Process with Long-Range Dependence. - Parthe Pandit; Mojtaba Sahraee-Ardakan; Arash A. Amini; Sundeep Rangan; Alyson K. Fletcher (CoRR, 2019)

Hierarchical Stochastic Block Model for Community Detection in Multiplex Networks. - Marina S. Paez; Arash A. Amini; Lizhen Lin (CoRR, 2019)

Spectrally-truncated kernel ridge regression and its free lunch. - Arash A. Amini (CoRR, 2019)

Concentration of kernel matrices with application to kernel spectral clustering. - Arash A. Amini; Zahra S. Razaee (CoRR, 2019)

Matched Bipartite Block Model with Covariates. - Zahra S. Razaee; Arash A. Amini; Jingyi Jessica Li (J. Mach. Learn. Res., 2019)

Analysis of spectral clustering algorithms for community detection: the general bipartite setting. - Zhixin Zhou; Arash A. Amini (J. Mach. Learn. Res., 2019)

The Potts-Ising model for discrete multivariate data. - Zahra S. Razaee; Arash A. Amini (NeurIPS, 2020)

Adjusted chi-square test for degree-corrected block models. - Linfan Zhang; Arash A. Amini (CoRR, 2020)

Optimal Bipartite Network Clustering. - Zhixin Zhou; Arash A. Amini (J. Mach. Learn. Res., 2020)

Generalized Autoregressive Linear Models for Discrete High-Dimensional Data. - Parthe Pandit; Mojtaba Sahraee-Ardakan; Arash A. Amini; Sundeep Rangan; Alyson K. Fletcher (IEEE J. Sel. Areas Inf. Theory, 2020)

Label consistency in overfitted generalized $k$-means. - Linfan Zhang; Arash A. Amini (NeurIPS, 2021)

Optimizing Regularized Cholesky Score for Order-Based Learning of Bayesian Networks. - Qiaoling Ye; Arash A. Amini; Qing Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

On perfectness in Gaussian graphical models. - Arash A. Amini; Bryon Aragam; Qing Zhou (AISTATS, 2022)

Target alignment in truncated kernel ridge regression. - Arash A. Amini; Richard Baumgartner; Dai Feng (NeurIPS, 2022)

Distributed Learning of Generalized Linear Causal Networks. - Qiaoling Ye; Arash A. Amini; Qing Zhou (CoRR, 2022)

Bayesian community detection for networks with covariates. - Luyi Shen; Arash A. Amini; Nathaniel Josephs; Lizhen Lin (CoRR, 2022)

A non-graphical representation of conditional independence via the neighbourhood lattice. - Arash A. Amini; Bryon Aragam; Qing Zhou (CoRR, 2022)

LapGM: A Multisequence MR Bias Correction and Normalization Model. - Luciano Vinas; Arash A. Amini; Jade Fischer; Atchar Sudhyadhom (CoRR, 2022)

Statistical Guarantees for Consensus Clustering. - Zhixin Zhou; Gautam Dudeja; Arash A. Amini (ICLR, 2023)

Nested stochastic block model for simultaneously clustering networks and nodes. - Nathaniel Josephs; Arash A. Amini; Marina S. Paez; Lizhen Lin (CoRR, 2023)

Simplifying GNN Performance with Low Rank Kernel Models. - Luciano Vinas; Arash A. Amini (CoRR, 2023)

Performance evaluation of automotive dealerships using grouped mixture of regressions. - Haidar Almohri; Ratna Babu Chinnam; Arash A. Amini (Expert Syst. Appl., 2023)

Simple GNNs With Low Rank Non-Parametric Aggregators. - Luciano Vinas; Arash A. Amini (LoG, 2024)

Graph Neural Thompson Sampling. - Shuang Wu; Arash A. Amini (RLJ, 2024)

Network two-sample test for block models. - Chung Kyong Nguen; Oscar Hernan Madrid Padilla; Arash A. Amini (CoRR, 2024)

Sharp Bounds for Poly-GNNs and the Effect of Graph Noise. - Luciano Vinas; Arash A. Amini (CoRR, 2024)

Federated Learning of Generalized Linear Causal Networks. - Qiaoling Ye; Arash A. Amini; Qing Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2024)