Search Results for author: Daniel Pimentel-Alarcón

Found 5 papers, 0 papers with code

Contrastive Learning with Orthonormal Anchors (CLOA)

no code implementations27 Mar 2024 Huanran Li, Daniel Pimentel-Alarcón

This study focuses on addressing the instability issues prevalent in contrastive learning, specifically examining the InfoNCE loss function and its derivatives.

Contrastive Learning

TransFusion: Contrastive Learning with Transformers

no code implementations27 Mar 2024 Huanran Li, Daniel Pimentel-Alarcón

This paper proposes a novel framework, TransFusion, designed to make the process of contrastive learning more analytical and explainable.

Contrastive Learning Data Augmentation

Fusion Subspace Clustering for Incomplete Data

no code implementations22 May 2022 Usman Mahmood, Daniel Pimentel-Alarcón

This paper introduces {\em fusion subspace clustering}, a novel method to learn low-dimensional structures that approximate large scale yet highly incomplete data.

Clustering Model Selection

Geometry of the Minimum Volume Confidence Sets

no code implementations16 Feb 2022 Heguang Lin, Mengze Li, Daniel Pimentel-Alarcón, Matthew Malloy

Prior work showed the minimum-volume confidence sets are the level-sets of a discontinuous function defined by an exact p-value.

Tensor Methods for Nonlinear Matrix Completion

no code implementations26 Apr 2018 Greg Ongie, Daniel Pimentel-Alarcón, Laura Balzano, Rebecca Willett, Robert D. Nowak

This approach will succeed in many cases where traditional LRMC is guaranteed to fail because the data are low-rank in the tensorized representation but not in the original representation.

Low-Rank Matrix Completion

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