Sparse PCA: Algorithms, Adversarial Perturbations and Certificates. - Tommaso d'Orsi; Pravesh K. Kothari; Gleb Novikov; David Steurer (FOCS, 2020)

Regress Consistently when Oblivious Outliers Overwhelm. - Tommaso d'Orsi; Gleb Novikov; David Steurer (CoRR, 2020)

Robust recovery for stochastic block models. - Jingqiu Ding; Tommaso d'Orsi; Rajai Nasser; David Steurer (FOCS, 2021)

Consistent regression when oblivious outliers overwhelm. - Tommaso d'Orsi; Gleb Novikov; David Steurer (ICML, 2021)

The Complexity of Sparse Tensor PCA. - Davin Choo; Tommaso d'Orsi (NeurIPS, 2021)

Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers. - Tommaso d'Orsi; Chih-Hung Liu 001; Rajai Nasser; Gleb Novikov; David Steurer; Stefan Tiegel (NeurIPS, 2021)

On the well-spread property and its relation to linear regression. - Hongjie Chen; Tommaso d'Orsi (COLT, 2022)

Fast algorithm for overcomplete order-3 tensor decomposition. - Jingqiu Ding; Tommaso d'Orsi; Chih-Hung Liu 001; David Steurer; Stefan Tiegel (COLT, 2022)

A Ihara-Bass Formula for Non-Boolean Matrices and Strong Refutations of Random CSPs. - Tommaso d'Orsi; Luca Trevisan 001 (CCC, 2023)

Reaching Kesten-Stigum Threshold in the Stochastic Block Model under Node Corruptions. - Yiding Hua; Jingqiu Ding; Tommaso d'Orsi; David Steurer (COLT, 2023)

Private estimation algorithms for stochastic block models and mixture models. - Hongjie Chen 004; Vincent Cohen-Addad; Tommaso d'Orsi; Alessandro Epasto; Jacob Imola; David Steurer; Stefan Tiegel (NeurIPS, 2023)

Higher degree sum-of-squares relaxations robust against oblivious outliers. - Tommaso d'Orsi; Rajai Nasser; Gleb Novikov; David Steurer (SODA, 2023)

Information-computation gaps in robust statistics. - Tommaso d'Orsi (2023)

Perturb-and-Project: Differentially Private Similarities and Marginals. - Vincent Cohen-Addad; Tommaso d'Orsi; Alessandro Epasto; Vahab Mirrokni; Peilin Zhong (ICML, 2024)

Multi-View Stochastic Block Models. - Vincent Cohen-Addad; Tommaso d'Orsi; Silvio Lattanzi; Rajai Nasser (ICML, 2024)

A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering. - Vincent Cohen-Addad; Tommaso d'Orsi; Aida Mousavifar (ICML, 2024)

Learning-Augmented Approximation Algorithms for Maximum Cut and Related Problems. - Vincent Cohen-Addad; Tommaso d'Orsi; Anupam Gupta 001; Euiwoong Lee; Debmalya Panigrahi (NeurIPS, 2024)

Private Graphon Estimation via Sum-of-Squares. - Hongjie Chen 004; Jingqiu Ding; Tommaso d'Orsi; Yiding Hua; Chih-Hung Liu 001; David Steurer (STOC, 2024)

Max-Cut with ε-Accurate Predictions. - Vincent Cohen-Addad; Tommaso d'Orsi; Anupam Gupta 001; Euiwoong Lee; Debmalya Panigrahi (CoRR, 2024)

On Finding Randomly Planted Cliques in Arbitrary Graphs. - Francesco Agrimonti; Marco Bressan 002; Tommaso d'Orsi (APPROX/RANDOM, 2025)

Sparsest Cut and Eigenvalue Multiplicities on Low Degree Abelian Cayley Graphs. - Tommaso d'Orsi; Chris Jones; Jake Ruotolo; Salil P. Vadhan; Jiyu Zhang (APPROX/RANDOM, 2025)