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Poster
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Thu 9:00
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Acceleration in Distributed Sparse Regression
Marie Maros · Gesualdo Scutari
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Poster
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Thu 14:00
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DGD^2: A Linearly Convergent Distributed Algorithm For High-dimensional Statistical Recovery
Marie Maros · Gesualdo Scutari
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Poster
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Tue 14:00
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Robust Testing in High-Dimensional Sparse Models
Anand Jerry George · Clément L Canonne
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Workshop
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Data-driven subgroup identification for linear regression
Zachary Izzo · Ruishan Liu · James Zou
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Poster
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Wed 9:00
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Interpolation and Regularization for Causal Learning
Leena Chennuru Vankadara · Luca Rendsburg · Ulrike Luxburg · Debarghya Ghoshdastidar
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Poster
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Thu 14:00
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What Can Transformers Learn In-Context? A Case Study of Simple Function Classes
Shivam Garg · Dimitris Tsipras · Percy Liang · Gregory Valiant
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Workshop
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Contrasting random and learned features in deep Bayesian linear regression
Jacob Zavatone-Veth · William Tong · Cengiz Pehlevan
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Workshop
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Group Excess Risk Bound of Overparameterized Linear Regression with Constant-Stepsize SGD
Arjun Subramonian · Levent Sagun · Kai-Wei Chang · Yizhou Sun
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Poster
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Thu 14:00
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A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Lijia Zhou · Frederic Koehler · Pragya Sur · Danica J. Sutherland · Nati Srebro
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Workshop
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Minimax Optimal Fair Regression under Linear Model
Kazuto Fukuchi · Jun Sakuma
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Poster
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Wed 9:00
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Hypothesis Testing for Differentially Private Linear Regression
Daniel Alabi · Salil Vadhan
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Poster
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Tue 14:00
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Semi-supervised Active Linear Regression
Nived Rajaraman · Fnu Devvrit · Pranjal Awasthi
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