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Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back
Neural Information Processing Systems (NeurIPS), 2016
15 August 2016
Vitaly Feldman
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Papers citing
"Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back"
44 / 44 papers shown
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Benign Underfitting of Stochastic Gradient Descent
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Yishay Mansour
Uri Sherman
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Jayadev Acharya
Gautam Kamath
A. Suresh
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478
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Geometry
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Hilal Asi
Vitaly Feldman
Tomer Koren
Kunal Talwar
257
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02 Mar 2021
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Tomer Koren
239
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SGD Generalizes Better Than GD (And Regularization Doesn't Help)
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296
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163
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256
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Vitaly Feldman
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348
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278
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309
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Kunal Talwar
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298
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Private Stochastic Convex Optimization with Optimal Rates
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Vitaly Feldman
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High probability generalization bounds for uniformly stable algorithms with nearly optimal rate
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J. Vondrák
315
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Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the
O
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T
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O
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Lijun Zhang
Zhi Zhou
278
32
0
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Generalization Bounds for Uniformly Stable Algorithms
Vitaly Feldman
J. Vondrák
230
98
0
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Robust descent using smoothed multiplicative noise
Matthew J. Holland
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191
28
0
15 Oct 2018
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions
Mingrui Liu
Xiaoxuan Zhang
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Rong Jin
Tianbao Yang
261
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0
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A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer
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Zhe Li
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166
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0
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Machine-mediated learning (ML), 2017
Matthew J. Holland
K. Ikeda
OOD
416
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0
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Empirical Risk Minimization for Stochastic Convex Optimization:
O
(
1
/
n
)
O(1/n)
O
(
1/
n
)
- and
O
(
1
/
n
2
)
O(1/n^2)
O
(
1/
n
2
)
-type of Risk Bounds
Annual Conference Computational Learning Theory (COLT), 2017
Lijun Zhang
Tianbao Yang
Rong Jin
256
52
0
07 Feb 2017
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