activity
20172025
most citedLearning Low-Dimensional Metrics

10 citations · 19 across the 14 of their papers we have counts for

collaborators
Showing 2022Show all

5 papers · 1 filter

cs.CL2022

Detect, Retrieve, Comprehend: A Flexible Framework for Zero-Shot Document-Level Question Answering

Tavish McDonald, Brian Tsan, Amar Saini +5

Researchers produce thousands of scholarly documents containing valuable technical knowledge. The community faces the laborious task of reading these documents to identify, extract…

stat.ML2022★ 1 cited

One for All: Simultaneous Metric and Preference Learning over Multiple Users

Gregory Canal, Blake Mason, Ramya Korlakai Vinayak +1

This paper investigates simultaneous preference and metric learning from a crowd of respondents. A set of items represented by -dimensional feature vectors and paired comparison…

cs.LG2022★ 1 cited

A Blessing of Dimensionality in Membership Inference through Regularization

Jasper Tan, Daniel LeJeune, Blake Mason +2

Is overparameterization a privacy liability? In this work, we study the effect that the number of parameters has on a classifier's vulnerability to membership inference attacks. We…

stat.ML2022

An Experimental Design Approach for Regret Minimization in Logistic Bandits

Blake Mason, Kwang-Sung Jun, Lalit Jain

In this work we consider the problem of regret minimization for logistic bandits. The main challenge of logistic bandits is reducing the dependence on a potentially large problem d…

stat.ML2022★ 3 cited

Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference

Jasper Tan, Blake Mason, Hamid Javadi +1

A surprising phenomenon in modern machine learning is the ability of a highly overparameterized model to generalize well (small error on the test data) even when it is trained to m…