6 citations · 8 across the 12 of their papers we have counts for
13 papers
How Closely Do LLM Reviews Align with Human Peer Review?
Abraham Camelo-Guerrero, Jairo Diaz-Rodriguez
Large language models (LLMs) are increasingly used to generate scientific reviews, yet existing evaluations rarely examine whether different providers align with both conference de…
Position: Ideas Should be the Center of Machine Learning Research
Jairo Diaz-Rodriguez
Machine learning research increasingly bifurcates into two disconnected modes: benchmark-driven engineering that prioritizes metrics over understanding, and idealized theory that o…
When Can Digital Personas Reliably Approximate Human Survey Findings?
Mumin Jia, Yilin Chen, Divya Sharma +1
Digital personas powered by Large Language Models (LLMs) are increasingly proposed as substitutes for human survey respondents, yet it remains unclear when they can reliably approx…
Unsupervised Text Segmentation via Kernel Change-Point Detection on Sentence Embeddings
Mumin Jia, Jairo Diaz-Rodriguez
Unsupervised text segmentation is crucial because boundary labels are expensive, subjective, and often fail to transfer across domains and granularity choices. We propose Embed-KCP…
Structured Output Regularization: a framework for few-shot transfer learning
Nicolas Ewen, Jairo Diaz-Rodriguez, Kelly Ramsay
Traditional transfer learning typically reuses large pre-trained networks by freezing some of their weights and adding task-specific layers. While this approach is computationally…
Consistent Kernel Change-Point Detection under m-Dependence for Text Segmentation
Jairo Diaz-Rodriguez, Mumin Jia
Kernel change-point detection (KCPD) has become a widely used tool for identifying structural changes in complex data. While existing theory establishes consistency under independe…
Summaries as Centroids for Interpretable and Scalable Text Clustering
Jairo Diaz-Rodriguez
We introduce k-NLPmeans and k-LLMmeans, text-clustering variants of k-means that periodically replace numeric centroids with textual summaries. The key idea, summary-as-centroid, r…
Tomographic reconstruction of a disease transmission landscape via GPS recorded random paths
Jairo Diaz-Rodriguez, Juan Pablo Gomez, Jeremy P. Orange +4
Identifying areas in a landscape where individuals have a higher likelihood of disease infection is key to managing diseases. Unlike conventional methods relying on ecological assu…
Adjoint-Free 4D-Var Methods Via Line Search Optimization For Non-Linear Data Assimilation
Elias Nin-Ruiz, Jairo Diaz-Rodriguez
This paper proposes two practical implementations of Four-Dimensional Variational (4D-Var) Ensemble Kalman Filter (4D-EnKF) methods for non-linear data assimilation. Our formulatio…
Thresholding tests
Sylvain Sardy, Caroline Giacobino, Jairo Diaz-Rodriguez
We derive a new class of statistical tests for generalized linear models based on thresholding point estimators. These tests can be employed whether the model includes more paramet…
Nonparametric estimation of galaxy cluster's emissivity and point source detection in astrophysics with two lasso penalties
Jairo Diaz-Rodriguez, Dominique Eckert, Hatef Monajemi +2
Astrophysicists are interested in recovering the 3D gas emissivity of a galaxy cluster from a 2D image taken by a telescope. A blurring phenomenon and presence of point sources mak…
Quantile universal threshold for model selection
Caroline Giacobino, Sylvain Sardy, Jairo Diaz-Rodriguez +1
Efficient recovery of a low-dimensional structure from high-dimensional data has been pursued in various settings including wavelet denoising, generalized linear models and low-ran…
Quantile universal threshold: model selection at the detection edge for high-dimensional linear regression
Jairo Diaz-Rodriguez, Sylvain Sardy
To estimate a sparse linear model from data with Gaussian noise, consilience from lasso and compressed sensing literatures is that thresholding estimators like lasso and the Dantzi…