SDS Seminar Series – Arian Maleki, Columbia University
Nov
13
2026
Nov
13
2026
Description
The Fall 2026 SDS Seminar Series continues on November 13th from 2:00 p.m. to 3:00 p.m. with Arian Maleki (Associate Professor, Department of Statistics, Columbia University). This event is in-person in the Avaya Room (POB 2.302).
Title: Accurate and efficient data point removal for high-dimensional settings.
Abstract: Consider a model trained with 𝑝 parameters from 𝑛 independent and identically distributed observations. To assess a data point’s impact on the model, we remove it from the dataset and aim to understand the model’s behavior when trained on the remaining data. This scenario is relevant in various classical and modern applications, including risk estimation, outlier detection, machine unlearning, and data valuation. Conventional approaches involve training the model on the remaining data, but these can be computationally demanding. Consequently, researchers often resort to approximate methods. This talk highlights that in high-dimensional settings, where 𝑝 is either larger than 𝑛 or at the same order, many approximation methods may prove ineffective. We will present and analyze an accurate approximation method tailored for high-dimensional regimes, elucidating the conditions for its accuracy. In the concluding part of the presentation, time permitting, we will briefly discuss some of the unresolved issues in this domain.
Location
Avaya Room (POB 2.302)
Share
Other Events in This Series
Oct
4
2024
SDS Seminar Series – Huiyan Sang, Texas A&M University
GS-BART: Graph Split Additive Decision Trees for Spatial and Network Data
2:00 pm – 3:00 pm • In Person
Speaker(s): Huiyan Sang
Oct
11
2024
SDS Seminar Series – Mingyuan Zhou, University of Texas at Austin
Building Faster, Better, and Safer Deep Generative Models via Score Identity Distillation
2:00 pm – 3:00 pm • In Person
Speaker(s): Mingyuan Zhou
Oct
18
2024
SDS Seminar Series – Sherry Zhang, University of Texas at Austin
Pivoting between Space and Time: Spatio-Temporal Analysis with Cubble
2:00 pm – 3:00 pm • In Person
Speaker(s): Sherry Zhang
Oct
25
2024
SDS Seminar Series – Matt Koslovsky, Colorado State University
Sparse Dirichlet-Multinomial Models
2:00 pm – 3:00 pm • In Person
Speaker(s): Matt Koslovsky
Nov
1
2024
SDS Seminar Series – Aaditya Ramdas, Carnegie Mellon University
A Game-Theoretic Theory of Statistical Evidence
2:00 pm – 3:00 pm • In Person
Speaker(s): Aaditya Ramdas
Nov
8
2024
SDS Seminar Series – Myungsoo Yoo, University of Texas at Austin
Dynamic Spatio-Temporal Model Integrating Physics for Fire Front Propagation
2:00 pm – 3:00 pm • In Person
Speaker(s): Myungsoo Yoo
Nov
15
2024
SDS Seminar Series – Rafael Irizarry, Harvard University
Twenty-Five Years of Data Science: Music, Genomics, and Public Health Surveillance
2:00 pm – 3:00 pm • In Person
Speaker(s): Rafael Irizarry
Mar
7
2025
SDS Seminar Series - Arun Kuchibhotla, Carnegie Mellon University
Adaptive Inference Techniques for Some Irregular Problems
2:00 pm – 3:00 pm • In Person
Speaker(s): Arun Kuchibhotla
Mar
28
2025
SDS Seminar Series – Po-Ling Loh, University of Cambridge
Differentially Private M-estimation via Noisy Optimization
2:00 pm – 3:00 pm • In Person
Speaker(s): Po-Ling Loh
Apr
18
2025
SDS Seminar Series – Richard Samworth, University of Cambridge
How Should We Do Linear Regression?
2:00 pm – 3:00 pm • In Person
Speaker(s): Richard Samworth
