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ORCIDDaniel L. Pimentel-Alarcón
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2020 – today
- 2024
[j4]Huanran Li
, Daniel L. Pimentel-Alarcón:
GrassCaré: Visualizing the Grassmannian on the Poincaré Disk. SN Comput. Sci. 5(3): 298 (2024)- [c26]Ben A. Kizaric, Daniel L. Pimentel-Alarcón:
Principle Component Trees and Their Persistent Homology. AAAI 2024: 13220-13229 - [c25]Jeremy S. Johnson, Huanran Li, Daniel L. Pimentel-Alarcón:
Fusion over the Grassmannian for High-Rank Matrix Completion. ISIT 2024: 1550-1555 - [c24]Huanran Li, Daniel L. Pimentel-Alarcón:
Group-Sparse Subspace Clustering with Elastic Stars. ISIT 2024: 1961-1966 - [i13]Huanran Li, Daniel L. Pimentel-Alarcón:
TransFusion: Contrastive Learning with Transformers. CoRR abs/2403.18681 (2024) - [i12]Huanran Li, Daniel L. Pimentel-Alarcón:
Contrastive Learning with Orthonormal Anchors (CLOA). CoRR abs/2403.18699 (2024) - 2023
- [c23]Huanran Li, Daniel L. Pimentel-Alarcón:
Visualizing Grassmannians via Poincare Embeddings. VISIGRAPP (3: IVAPP) 2023: 27-39 - 2022
- [c22]Ben A. Kizaric, Daniel L. Pimentel-Alarcón:
Classifying Incomplete Data with a Mixture of Subspace Experts. Allerton 2022: 1-8 - [c21]Huanran Li, Daniel L. Pimentel-Alarcón:
Minimum-Length Trace Reconstruction via Integer Programming. Allerton 2022: 1-8 - [c20]Usman Mahmood, Daniel L. Pimentel-Alarcón:
Fusion Subspace Clustering for Incomplete Data. IJCNN 2022: 1-8 - [c19]Karan Srivastava, Daniel L. Pimentel-Alarcón:
A Perturbation Bound on the Subspace Estimator from Canonical Projections. ISIT 2022: 1617-1622 - [c18]Heguang Lin, Mengze Li, Daniel L. Pimentel-Alarcón, Matthew L. Malloy:
Geometry of the Minimum Volume Confidence Sets. ISIT 2022: 3180-3185 - [i11]Heguang Lin, Mengze Li, Daniel L. Pimentel-Alarcón, Matthew Malloy:
Geometry of the Minimum Volume Confidence Sets. CoRR abs/2202.08180 (2022) - [i10]Usman Mahmood, Daniel L. Pimentel-Alarcón:
Fusion Subspace Clustering for Incomplete Data. CoRR abs/2205.10872 (2022) - [i9]Karan Srivastava, Daniel L. Pimentel-Alarcón:
A Perturbation Bound on the Subspace Estimator from Canonical Projections. CoRR abs/2206.14278 (2022) - 2021
- [j3]Greg Ongie, Daniel L. Pimentel-Alarcón, Laura Balzano, Rebecca Willett, Robert D. Nowak:
Tensor Methods for Nonlinear Matrix Completion. SIAM J. Math. Data Sci. 3(1): 253-279 (2021) - [c17]Alejandro Pimentel-Alarcón, Daniel L. Pimentel-Alarcón:
Mixed-Features Vectors and Subspace Splitting. ICLR 2021 - [i8]Yuren Sun, Tatiana Midori Maeda, Claudia R. Solís-Lemus, Daniel L. Pimentel-Alarcón, Zuzana Burivalova:
Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural Networks. CoRR abs/2111.14971 (2021)
2010 – 2019
- 2019
- [c16]Md Mahfuzur Rahman, Daniel L. Pimentel-Alarcón:
GLIMPS: A Greedy Mixed-Integer Approach for Super Robust Matched Subspace Detection. Allerton 2019: 360-367 - [i7]Md Mahfuzur Rahman, Daniel L. Pimentel-Alarcón:
GLIMPS: A Greedy Mixed Integer Approach for Super Robust Matched Subspace Detection. CoRR abs/1910.13089 (2019) - 2018
- [c15]Claudia R. Solís-Lemus, Daniel L. Pimentel-Alarcón:
Breaking the Limits of Subspace Inference. Allerton 2018: 654-661 - [c14]Daniel L. Pimentel-Alarcón:
Mixture Matrix Completion. NeurIPS 2018: 2197-2207 - [i6]Greg Ongie, Laura Balzano, Daniel L. Pimentel-Alarcón, Rebecca Willett, Robert D. Nowak:
Tensor Methods for Nonlinear Matrix Completion. CoRR abs/1804.10266 (2018) - [i5]Daniel L. Pimentel-Alarcón:
Mixture Matrix Completion. CoRR abs/1808.00616 (2018) - [i4]Daniel L. Pimentel-Alarcón, Usman Mahmood:
Fusion Subspace Clustering: Full and Incomplete Data. CoRR abs/1808.00628 (2018) - 2017
- [c13]Daniel L. Pimentel-Alarcón, Robert D. Nowak:
Random Consensus Robust PCA. AISTATS 2017: 344-352 - [c12]Daniel L. Pimentel-Alarcón, Gregory Ongie, Laura Balzano, Rebecca Willett, Robert D. Nowak:
Low algebraic dimension matrix completion. Allerton 2017: 790-797 - [c11]Daniel L. Pimentel-Alarcón, Aritra Biswas, Claudia R. Solís-Lemus:
Adversarial principal component analysis. ISIT 2017: 2363-2367 - 2016
- [j2]Daniel L. Pimentel-Alarcón, Nigel Boston, Robert D. Nowak:
A Characterization of Deterministic Sampling Patterns for Low-Rank Matrix Completion. IEEE J. Sel. Top. Signal Process. 10(4): 623-636 (2016) - [j1]Daniel L. Pimentel-Alarcón, Nigel Boston, Robert D. Nowak:
Corrections to "A Characterization of Deterministic Sampling Patterns for Low-Rank Matrix Completion". IEEE J. Sel. Top. Signal Process. 10(8): 1567 (2016) - [c10]Daniel L. Pimentel-Alarcón:
A simpler approach to low-rank tensor canonical polyadic decomposition. Allerton 2016: 474-481 - [c9]Daniel L. Pimentel-Alarcón, Laura Balzano, Robert D. Nowak:
Necessary and sufficient conditions for sketched subspace clustering. Allerton 2016: 1335-1343 - [c8]Daniel L. Pimentel-Alarcón, Robert D. Nowak:
The Information-Theoretic Requirements of Subspace Clustering with Missing Data. ICML 2016: 802-810 - [c7]Daniel L. Pimentel-Alarcón, Robert D. Nowak:
A converse to low-rank matrix completion. ISIT 2016: 96-100 - [c6]Daniel L. Pimentel-Alarcón, Claudia R. Solís-Lemus:
Crime Detection via Crowdsourcing. MCPR 2016: 313-323 - [c5]Daniel L. Pimentel-Alarcón, Laura Balzano, Roummel F. Marcia, Robert D. Nowak, Rebecca Willett:
Group-sparse subspace clustering with missing data. SSP 2016: 1-5 - 2015
- [c4]Daniel L. Pimentel-Alarcón, Nigel Boston, Robert D. Nowak:
A characterization of deterministic sampling patterns for low-rank matrix completion. Allerton 2015: 1075-1082 - [c3]Daniel L. Pimentel-Alarcón, Robert D. Nowak:
Adaptive strategy for restricted-sampling noisy low-rank matrix completion. CAMSAP 2015: 429-432 - [c2]Daniel L. Pimentel-Alarcón, Nigel Boston, Robert D. Nowak:
Deterministic conditions for subspace identifiability from incomplete sampling. ISIT 2015: 2191-2195 - [i3]Daniel L. Pimentel-Alarcón, Nigel Boston, Robert D. Nowak:
A Characterization of Deterministic Sampling Patterns for Low-Rank Matrix Completion. CoRR abs/1503.02596 (2015) - 2014
- [c1]Daniel L. Pimentel-Alarcón, Robert D. Nowak, Laura Balzano:
On the sample complexity of subspace clustering with missing data. SSP 2014: 280-283 - [i2]Daniel L. Pimentel-Alarcón:
To lie or not to lie in a subspace. CoRR abs/1408.5544 (2014) - [i1]Daniel L. Pimentel-Alarcón, Robert D. Nowak, Nigel Boston:
Deterministic Conditions for Subspace Identifiability from Incomplete Sampling. CoRR abs/1410.0633 (2014)
Coauthor Index
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last updated on 2024-10-13 18:04 CEST by the dblp team
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