Poster

Thu 9:00

Acceleration in Distributed Sparse Regression
Marie Maros · Gesualdo Scutari

Poster

Thu 14:00

DGD^2: A Linearly Convergent Distributed Algorithm For High-dimensional Statistical Recovery
Marie Maros · Gesualdo Scutari

Poster

Tue 14:00

Robust Testing in High-Dimensional Sparse Models
Anand Jerry George · Clément L Canonne

Workshop

Data-driven subgroup identification for linear regression
Zachary Izzo · Ruishan Liu · James Zou

Poster

Wed 9:00

Interpolation and Regularization for Causal Learning
Leena Chennuru Vankadara · Luca Rendsburg · Ulrike Luxburg · Debarghya Ghoshdastidar

Workshop

Group Excess Risk Bound of Overparameterized Linear Regression with Constant-Stepsize SGD
Arjun Subramonian · Levent Sagun · Kai-Wei Chang · Yizhou Sun

Poster

Thu 14:00

What Can Transformers Learn In-Context? A Case Study of Simple Function Classes
Shivam Garg · Dimitris Tsipras · Percy Liang · Gregory Valiant

Workshop

Contrasting random and learned features in deep Bayesian linear regression
Jacob Zavatone-Veth · William Tong · Cengiz Pehlevan

Poster

Thu 14:00

A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Lijia Zhou · Frederic Koehler · Pragya Sur · Danica J. Sutherland · Nati Srebro

Workshop

Minimax Optimal Fair Regression under Linear Model
Kazuto Fukuchi · Jun Sakuma

Poster

Wed 9:00

Hypothesis Testing for Differentially Private Linear Regression
Daniel Alabi · Salil Vadhan

Poster

Tue 14:00

Semi-supervised Active Linear Regression
Nived Rajaraman · Fnu Devvrit · Pranjal Awasthi