Daniel L. Pimentel-Alarcón

According to our database1, Daniel L. Pimentel-Alarcón authored at least 32 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
GrassCaré: Visualizing the Grassmannian on the Poincaré Disk.
SN Comput. Sci., March, 2024

Contrastive Learning with Orthonormal Anchors (CLOA).
CoRR, 2024

TransFusion: Contrastive Learning with Transformers.
CoRR, 2024

Principle Component Trees and Their Persistent Homology.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Visualizing Grassmannians via Poincare Embeddings.
Proceedings of the 18th International Joint Conference on Computer Vision, 2023

2022
A Perturbation Bound on the Subspace Estimator from Canonical Projections.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Geometry of the Minimum Volume Confidence Sets.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Fusion Subspace Clustering for Incomplete Data.
Proceedings of the International Joint Conference on Neural Networks, 2022

Minimum-Length Trace Reconstruction via Integer Programming.
Proceedings of the 58th Annual Allerton Conference on Communication, 2022

Classifying Incomplete Data with a Mixture of Subspace Experts.
Proceedings of the 58th Annual Allerton Conference on Communication, 2022

2021
Tensor Methods for Nonlinear Matrix Completion.
SIAM J. Math. Data Sci., 2021

Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural Networks.
CoRR, 2021

Mixed-Features Vectors and Subspace Splitting.
Proceedings of the 9th International Conference on Learning Representations, 2021

2019
GLIMPS: A Greedy Mixed-Integer Approach for Super Robust Matched Subspace Detection.
Proceedings of the 57th Annual Allerton Conference on Communication, 2019

2018
Fusion Subspace Clustering: Full and Incomplete Data.
CoRR, 2018

Mixture Matrix Completion.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Breaking the Limits of Subspace Inference.
Proceedings of the 56th Annual Allerton Conference on Communication, 2018

2017
Adversarial principal component analysis.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Low algebraic dimension matrix completion.
Proceedings of the 55th Annual Allerton Conference on Communication, 2017

Random Consensus Robust PCA.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Corrections to "A Characterization of Deterministic Sampling Patterns for Low-Rank Matrix Completion".
IEEE J. Sel. Top. Signal Process., 2016

A Characterization of Deterministic Sampling Patterns for Low-Rank Matrix Completion.
IEEE J. Sel. Top. Signal Process., 2016

Group-sparse subspace clustering with missing data.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Crime Detection via Crowdsourcing.
Proceedings of the Pattern Recognition - 8th Mexican Conference, 2016

A converse to low-rank matrix completion.
Proceedings of the IEEE International Symposium on Information Theory, 2016

The Information-Theoretic Requirements of Subspace Clustering with Missing Data.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Necessary and sufficient conditions for sketched subspace clustering.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016

A simpler approach to low-rank tensor canonical polyadic decomposition.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2015
Deterministic conditions for subspace identifiability from incomplete sampling.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Adaptive strategy for restricted-sampling noisy low-rank matrix completion.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

2014
To lie or not to lie in a subspace.
CoRR, 2014

On the sample complexity of subspace clustering with missing data.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014


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