On the sample complexity of subspace clustering with missing data. - Daniel L. Pimentel-Alarcón; Robert D. Nowak; Laura Balzano (SSP, 2014)

To lie or not to lie in a subspace. - Daniel L. Pimentel-Alarcón (CoRR, 2014)

Adaptive strategy for restricted-sampling noisy low-rank matrix completion. - Daniel L. Pimentel-Alarcón; Robert D. Nowak (CAMSAP, 2015)

Deterministic conditions for subspace identifiability from incomplete sampling. - Daniel L. Pimentel-Alarcón; Nigel Boston; Robert D. Nowak (ISIT, 2015)

A simpler approach to low-rank tensor canonical polyadic decomposition. - Daniel L. Pimentel-Alarcón (Allerton, 2016)

Necessary and sufficient conditions for sketched subspace clustering. - Daniel L. Pimentel-Alarcón; Laura Balzano; Robert D. Nowak (Allerton, 2016)

The Information-Theoretic Requirements of Subspace Clustering with Missing Data. - Daniel L. Pimentel-Alarcón; Robert D. Nowak (ICML, 2016)

A converse to low-rank matrix completion. - Daniel L. Pimentel-Alarcón; Robert D. Nowak (ISIT, 2016)

Crime Detection via Crowdsourcing. - Daniel L. Pimentel-Alarcón; Claudia R. Solís-Lemus (MCPR, 2016)

Group-sparse subspace clustering with missing data. - Daniel L. Pimentel-Alarcón; Laura Balzano; Roummel F. Marcia; Robert D. Nowak; Rebecca Willett (SSP, 2016)

A Characterization of Deterministic Sampling Patterns for Low-Rank Matrix Completion. - Daniel L. Pimentel-Alarcón; Nigel Boston; Robert D. Nowak (IEEE J. Sel. Top. Signal Process., 2016)

Corrections to "A Characterization of Deterministic Sampling Patterns for Low-Rank Matrix Completion". - Daniel L. Pimentel-Alarcón; Nigel Boston; Robert D. Nowak (IEEE J. Sel. Top. Signal Process., 2016)

Random Consensus Robust PCA. - Daniel L. Pimentel-Alarcón; Robert D. Nowak (AISTATS, 2017)

Low algebraic dimension matrix completion. - Daniel L. Pimentel-Alarcón; Gregory Ongie; Laura Balzano; Rebecca Willett; Robert D. Nowak (Allerton, 2017)

Adversarial principal component analysis. - Daniel L. Pimentel-Alarcón; Aritra Biswas; Claudia R. Solís-Lemus (ISIT, 2017)

Breaking the Limits of Subspace Inference. - Claudia R. Solís-Lemus; Daniel L. Pimentel-Alarcón (Allerton, 2018)

Mixture Matrix Completion. - Daniel L. Pimentel-Alarcón (NeurIPS, 2018)

Fusion Subspace Clustering: Full and Incomplete Data. - Daniel L. Pimentel-Alarcón; Usman Mahmood (CoRR, 2018)

GLIMPS: A Greedy Mixed-Integer Approach for Super Robust Matched Subspace Detection. - Md Mahfuzur Rahman; Daniel L. Pimentel-Alarcón (Allerton, 2019)

Mixed-Features Vectors and Subspace Splitting. - Alejandro Pimentel-Alarcón; Daniel L. Pimentel-Alarcón (ICLR, 2021)

Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural Networks. - Yuren Sun; Tatiana Midori Maeda; Claudia R. Solís-Lemus; Daniel L. Pimentel-Alarcón; Zuzana Burivalova (CoRR, 2021)

Tensor Methods for Nonlinear Matrix Completion. - Greg Ongie; Daniel L. Pimentel-Alarcón; Laura Balzano; Rebecca Willett; Robert D. Nowak (SIAM J. Math. Data Sci., 2021)

Classifying Incomplete Data with a Mixture of Subspace Experts. - Ben A. Kizaric; Daniel L. Pimentel-Alarcón (Allerton, 2022)

Minimum-Length Trace Reconstruction via Integer Programming. - Huanran Li; Daniel L. Pimentel-Alarcón (Allerton, 2022)

Fusion Subspace Clustering for Incomplete Data. - Usman Mahmood; Daniel L. Pimentel-Alarcón (IJCNN, 2022)

Geometry of the Minimum Volume Confidence Sets. - Heguang Lin; Mengze Li 003; Daniel L. Pimentel-Alarcón; Matthew L. Malloy (ISIT, 2022)

A Perturbation Bound on the Subspace Estimator from Canonical Projections. - Karan Srivastava; Daniel L. Pimentel-Alarcón (ISIT, 2022)

Visualizing Grassmannians via Poincare Embeddings. - Huanran Li; Daniel L. Pimentel-Alarcón (VISIGRAPP (3: IVAPP), 2023)

Principle Component Trees and Their Persistent Homology. - Ben A. Kizaric; Daniel L. Pimentel-Alarcón (AAAI, 2024)

Fusion over the Grassmannian for High-Rank Matrix Completion. - Jeremy S. Johnson; Huanran Li; Daniel L. Pimentel-Alarcón (ISIT, 2024)

Group-Sparse Subspace Clustering with Elastic Stars. - Huanran Li; Daniel L. Pimentel-Alarcón (ISIT, 2024)

TransFusion: Contrastive Learning with Transformers. - Huanran Li; Daniel L. Pimentel-Alarcón (CoRR, 2024)

Contrastive Learning with Orthonormal Anchors (CLOA). - Huanran Li; Daniel L. Pimentel-Alarcón (CoRR, 2024)

GrassCaré: Visualizing the Grassmannian on the Poincaré Disk. - Huanran Li; Daniel L. Pimentel-Alarcón (SN Comput. Sci., 2024)

Deep-Union Completion. - Siddharth Baskar; Karan Vikyath Veeranna Rupashree; Daniel L. Pimentel-Alarcón (AAAI, 2025)

An Integer Programming Approach to Subspace Clustering with Missing Data. - Akhilesh Soni; Jeff T. Linderoth; James R. Luedtke; Daniel L. Pimentel-Alarcón (INFORMS J. Optim., 2025)