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Datamodels: Predicting Predictions from Training Data

Datamodels: Predicting Predictions from Training Data

1 February 2022
Andrew Ilyas
Sung Min Park
Logan Engstrom
Guillaume Leclerc
A. Madry
    TDI
ArXivPDFHTML

Papers citing "Datamodels: Predicting Predictions from Training Data"

13 / 113 papers shown
Title
The Privacy Onion Effect: Memorization is Relative
The Privacy Onion Effect: Memorization is Relative
Nicholas Carlini
Matthew Jagielski
Chiyuan Zhang
Nicolas Papernot
Andreas Terzis
Florian Tramèr
PILM
MIACV
33
99
0
21 Jun 2022
Measuring the Effect of Training Data on Deep Learning Predictions via
  Randomized Experiments
Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments
Jinkun Lin
Anqi Zhang
Mathias Lécuyer
Jinyang Li
Aurojit Panda
S. Sen
TDI
FedML
29
52
0
20 Jun 2022
On the Permanence of Backdoors in Evolving Models
On the Permanence of Backdoors in Evolving Models
Huiying Li
A. Bhagoji
Yuxin Chen
Haitao Zheng
Ben Y. Zhao
AAML
29
2
0
08 Jun 2022
Data Banzhaf: A Robust Data Valuation Framework for Machine Learning
Data Banzhaf: A Robust Data Valuation Framework for Machine Learning
Jiachen T. Wang
R. Jia
FedML
TDI
52
94
0
30 May 2022
Interpolating Compressed Parameter Subspaces
Interpolating Compressed Parameter Subspaces
Siddhartha Datta
N. Shadbolt
37
5
0
19 May 2022
Exploring Transformer Backbones for Heterogeneous Treatment Effect
  Estimation
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation
Yi-Fan Zhang
Hanlin Zhang
Zachary Chase Lipton
Li Erran Li
Eric P. Xing
OODD
24
29
0
02 Feb 2022
Counterfactual Memorization in Neural Language Models
Counterfactual Memorization in Neural Language Models
Chiyuan Zhang
Daphne Ippolito
Katherine Lee
Matthew Jagielski
Florian Tramèr
Nicholas Carlini
32
128
0
24 Dec 2021
ModelPred: A Framework for Predicting Trained Model from Training Data
ModelPred: A Framework for Predicting Trained Model from Training Data
Yingyan Zeng
Jiachen T. Wang
Si-An Chen
H. Just
Ran Jin
R. Jia
TDI
MU
33
2
0
24 Nov 2021
Deduplicating Training Data Makes Language Models Better
Deduplicating Training Data Makes Language Models Better
Katherine Lee
Daphne Ippolito
A. Nystrom
Chiyuan Zhang
Douglas Eck
Chris Callison-Burch
Nicholas Carlini
SyDa
242
593
0
14 Jul 2021
Extracting Training Data from Large Language Models
Extracting Training Data from Large Language Models
Nicholas Carlini
Florian Tramèr
Eric Wallace
Matthew Jagielski
Ariel Herbert-Voss
...
Tom B. Brown
D. Song
Ulfar Erlingsson
Alina Oprea
Colin Raffel
MLAU
SILM
290
1,815
0
14 Dec 2020
When is Memorization of Irrelevant Training Data Necessary for
  High-Accuracy Learning?
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning?
Gavin Brown
Mark Bun
Vitaly Feldman
Adam D. Smith
Kunal Talwar
253
93
0
11 Dec 2020
An Investigation of Why Overparameterization Exacerbates Spurious
  Correlations
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa
Aditi Raghunathan
Pang Wei Koh
Percy Liang
152
371
0
09 May 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,661
0
05 Dec 2016
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