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Workshop
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HoloNets: Spectral Convolutions do extend to Directed Graphs
Christian Koke · Daniel Cremers
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Poster
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Tue 15:15
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Refined Mechanism Design for Approximately Structured Priors via Active Regression
Christos Boutsikas · Petros Drineas · Marios Mertzanidis · Alexandros Psomas · Paritosh Verma
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Poster
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The noise level in linear regression with dependent data
Ingvar Ziemann · Stephen Tu · George J. Pappas · Nikolai Matni
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Poster
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Wed 8:45
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Adaptive Principal Component Regression with Applications to Panel Data
Anish Agarwal · Keegan Harris · Justin Whitehouse · Steven Wu
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Poster
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Wed 15:00
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Errors-in-variables Fr\'echet Regression with Low-rank Covariate Approximation
Dogyoon Song · Kyunghee Han
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Poster
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Tue 15:15
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Optimal Excess Risk Bounds for Empirical Risk Minimization on p-Norm Linear Regression
Ayoub El Hanchi · Murat Erdogdu
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Poster
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Tue 15:15
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FIRAL: An Active Learning Algorithm for Multinomial Logistic Regression
Youguang Chen · George Biros
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Poster
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Tue 15:15
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New Bounds for Hyperparameter Tuning of Regression Problems Across Instances
Maria-Florina Balcan · Anh Nguyen · Dravyansh Sharma
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Poster
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Tue 15:15
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Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression
Jing Xu · Jiaye Teng · Yang Yuan · Andrew Yao
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Poster
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Thu 15:00
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Distribution-Free Model-Agnostic Regression Calibration via Nonparametric Methods
Shang Liu · Zhongze Cai · Xiaocheng Li
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Poster
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Tue 8:45
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Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability
Jingfeng Wu · Vladimir Braverman · Jason Lee
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Poster
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Thu 8:45
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Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression
Ilias Diakonikolas · Daniel Kane · Ankit Pensia · Ankit Pensia · Thanasis Pittas
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