Niladri Chatterji
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Type
Conference paper
Journal article
Preprint
Date
2022
2021
2020
2019
2018
2017
2014
Liang et al.
(2022).
Holistic evaluation of language models
.
PDF
Niladri S. Chatterji
,
Philip M. Long
(2022).
Deep linear networks can benignly overfit when shallow ones do
.
PDF
Niladri S. Chatterji*
,
Saminul Haque*
,
Tatsunori Hashimoto
(2022).
Undersampling is a minimax optimal robustness intervention in nonparametric classification
.
PDF
Spencer Frei
,
Niladri S. Chatterji
,
Peter L. Bartlett
(2022).
Random feature amplification: Feature learning and generalization in neural networks
.
PDF
Spencer Frei
,
Niladri S. Chatterji
,
Peter L. Bartlett
(2022).
Benign overfitting without linearity: Neural network classifiers trained by gradient descent for noisy linear data
.
PDF
Ke Alexander Wang*
,
Niladri S. Chatterji*
,
Saminul Haque
,
Tatsunori Hashimoto
(2021).
Is importance weighting incompatible with interpolating classifiers?
.
PDF
Niladri S. Chatterji
,
Philip M. Long
(2021).
Foolish crowds support benign overfitting
.
PDF
Niladri S. Chatterji
,
Philip M. Long
,
Peter L. Bartlett
(2021).
The interplay between implicit bias and benign overfitting in two-layer linear networks
.
PDF
Bommasani et al.
(2021).
On the opportunities and risks of foundation models
.
PDF
Niladri S. Chatterji*
,
Aldo Pacchiano*
,
Peter L. Bartlett
,
Michael I. Jordan
(2021).
On the theory of reinforcement learning with once-per-episode feedback
.
PDF
Niladri S. Chatterji
,
Philip M. Long
,
Peter L. Bartlett
(2021).
When does gradient descent with logistic loss interpolate using deep networks with smoothed ReLU activations?
.
PDF
Niladri S. Chatterji
,
Philip M. Long
,
Peter L. Bartlett
(2020).
When does gradient descent with logistic loss find interpolating two-layer networks?
.
PDF
Niladri S. Chatterji
,
Philip M. Long
(2020).
Finite-sample analysis of interpolating linear classifiers in the overparameterized regime
.
PDF
Niladri S. Chatterji
,
Peter L. Bartlett
,
Philip M. Long
(2020).
Oracle lower bounds for stochastic gradient Markov chain Monte Carlo methods
.
PDF
Niladri S. Chatterji
,
Behnam Neyshabur
,
Hanie Sedghi
(2019).
The intriguing role of module criticality in the generalization of deep networks
.
PDF
Niladri S. Chatterji*
,
Jelena Diakonikolas*
,
Michael I. Jordan
,
Peter L. Bartlett
(2019).
Langevin Monte Carlo without smoothness
.
PDF
Niladri S. Chatterji
,
Vidya Muthukumar
,
Peter L. Bartlett
(2019).
OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits
.
PDF
Yi-An Ma
,
Niladri S. Chatterji
,
Xiang Cheng
,
Nicolas Flammarion
,
Peter L. Bartlett
,
Michael I. Jordan
(2019).
Is there an analog of Nesterov acceleration for MCMC?
.
PDF
Xiang Cheng
,
Niladri S. Chatterji
,
Yasin Abbasi-Yadkori
,
Peter L. Bartlett
,
Michael I. Jordan
(2018).
Convergence rates for Langevin Monte Carlo in the nonconvex setting
.
PDF
Aldo Pacchiano*
,
Niladri S. Chatterji*
,
Peter L. Bartlett
(2018).
Online learning with kernel losses
. In
ICML 2019
.
PDF
Niladri S. Chatterji
,
Nicolas Flammarion
,
Yi-An Ma
,
Peter L. Bartlett
,
Michael I. Jordan
(2018).
On the theory of variance reduction for stochastic gradient Monte Carlo
. In
ICML 2018
.
PDF
Xiang Cheng*
,
Niladri S. Chatterji*
,
Peter L. Bartlett
,
Michael I. Jordan
(2017).
Underdamped Langevin MCMC: A non-asymptotic analysis
. In
COLT 2018
.
PDF
Niladri S. Chatterji
,
Peter L. Bartlett
(2017).
Alternating minimization for dictionary learning: Local convergence guarantees
. In
COLT 2017
.
PDF
Niladri S. Chatterji
,
Ashwin Tulapurkar
,
Bhaskaran Muralidharan
(2014).
Enhancement of spin-transfer torque switching via resonant tunneling
. In “APL”.
PDF
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