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Logistic Regression: The Importance of Being Improper
v1v2 (latest)

Logistic Regression: The Importance of Being Improper

25 March 2018
Dylan J. Foster
Satyen Kale
Haipeng Luo
M. Mohri
Karthik Sridharan
ArXiv (abs)PDFHTML

Papers citing "Logistic Regression: The Importance of Being Improper"

24 / 24 papers shown
Title
Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability
Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability
Yu Zhang
Peng Zhao
Masashi Sugiyama
115
0
0
12 Jun 2025
Bandit and Delayed Feedback in Online Structured Prediction
Bandit and Delayed Feedback in Online Structured Prediction
Yuki Shibukawa
Taira Tsuchiya
Shinsaku Sakaue
Kenji Yamanishi
OffRL
111
0
0
26 Feb 2025
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Junghyun Lee
Se-Young Yun
Kwang-Sung Jun
197
6
0
19 Jul 2024
Online Platt Scaling with Calibeating
Online Platt Scaling with Calibeating
Chirag Gupta
Aaditya Ramdas
53
5
0
28 Apr 2023
Smoothed Analysis of Sequential Probability Assignment
Smoothed Analysis of Sequential Probability Assignment
Alankrita Bhatt
Nika Haghtalab
Abhishek Shetty
80
10
0
08 Mar 2023
Exploring Local Norms in Exp-concave Statistical Learning
Exploring Local Norms in Exp-concave Statistical Learning
Nikita Puchkin
Nikita Zhivotovskiy
149
2
0
21 Feb 2023
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization
Zakaria Mhammedi
Khashayar Gatmiry
57
7
0
02 Nov 2022
Anytime Valid Tests of Conditional Independence Under Model-X
Anytime Valid Tests of Conditional Independence Under Model-X
Peter Grünwald
A. Henzi
Tyron Lardy
108
19
0
26 Sep 2022
Blessing of Class Diversity in Pre-training
Blessing of Class Diversity in Pre-training
Yulai Zhao
Jianshu Chen
S. Du
AI4CE
77
3
0
07 Sep 2022
A Contrastive Approach to Online Change Point Detection
A Contrastive Approach to Online Change Point Detection
Artur Goldman
Nikita Puchkin
Valeriia Shcherbakova
Uliana Vinogradova
82
7
0
21 Jun 2022
Scale-free Unconstrained Online Learning for Curved Losses
Scale-free Unconstrained Online Learning for Curved Losses
J. Mayo
Hédi Hadiji
T. Erven
82
13
0
11 Feb 2022
Fast Rates for Nonparametric Online Learning: From Realizability to
  Learning in Games
Fast Rates for Nonparametric Online Learning: From Realizability to Learning in Games
C. Daskalakis
Noah Golowich
55
24
0
17 Nov 2021
Efficient Methods for Online Multiclass Logistic Regression
Efficient Methods for Online Multiclass Logistic Regression
Naman Agarwal
Satyen Kale
Julian Zimmert
60
10
0
06 Oct 2021
A Minimax Lower Bound for Low-Rank Matrix-Variate Logistic Regression
A Minimax Lower Bound for Low-Rank Matrix-Variate Logistic Regression
Batoul Taki
Mohsen Ghassemi
Anand D. Sarwate
W. Bajwa
42
3
0
31 May 2021
On Misspecification in Prediction Problems and Robustness via Improper
  Learning
On Misspecification in Prediction Problems and Robustness via Improper Learning
A. Marsden
John C. Duchi
Gregory Valiant
27
1
0
13 Jan 2021
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term
  Memory
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory
Paria Rashidinejad
Jiantao Jiao
Stuart J. Russell
72
11
0
12 Oct 2020
Efficient improper learning for online logistic regression
Efficient improper learning for online logistic regression
Rémi Jézéquel
Pierre Gaillard
Alessandro Rudi
101
23
0
18 Mar 2020
Strength from Weakness: Fast Learning Using Weak Supervision
Strength from Weakness: Fast Learning Using Weak Supervision
Joshua Robinson
Stefanie Jegelka
S. Sra
67
32
0
19 Feb 2020
No-regret Exploration in Contextual Reinforcement Learning
No-regret Exploration in Contextual Reinforcement Learning
Aditya Modi
Ambuj Tewari
OffRL
58
14
0
14 Mar 2019
Beyond Least-Squares: Fast Rates for Regularized Empirical Risk
  Minimization through Self-Concordance
Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance
Ulysse Marteau-Ferey
Dmitrii Ostrovskii
Francis R. Bach
Alessandro Rudi
188
52
0
08 Feb 2019
Orthogonal Statistical Learning
Orthogonal Statistical Learning
Dylan J. Foster
Vasilis Syrgkanis
164
174
0
25 Jan 2019
Finite-sample analysis of M-estimators using self-concordance
Finite-sample analysis of M-estimators using self-concordance
Dmitrii Ostrovskii
Francis R. Bach
87
52
0
16 Oct 2018
Online Multiclass Boosting with Bandit Feedback
Online Multiclass Boosting with Bandit Feedback
Daniel T. Zhang
Young Hun Jung
Ambuj Tewari
48
7
0
11 Oct 2018
Contextual bandits with surrogate losses: Margin bounds and efficient
  algorithms
Contextual bandits with surrogate losses: Margin bounds and efficient algorithms
Dylan J. Foster
A. Krishnamurthy
167
18
0
28 Jun 2018
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