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Learning from Aggregate responses: Instance Level versus Bag Level Loss
  Functions

Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions

20 January 2024
Adel Javanmard
Lin Chen
Vahab Mirrokni
Ashwinkumar Badanidiyuru
Gang Fu
ArXiv (abs)PDFHTML

Papers citing "Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions"

17 / 17 papers shown
Title
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses
Adel Javanmard
Matthew Fahrbach
Vahab Mirrokni
56
3
0
07 Feb 2024
Learning from Aggregated Data: Curated Bags versus Random Bags
Learning from Aggregated Data: Curated Bags versus Random Bags
Lin Chen
Gang Fu
Amin Karbasi
Vahab Mirrokni
FedML
60
10
0
16 May 2023
Easy Learning from Label Proportions
Easy Learning from Label Proportions
R. Busa-Fekete
Heejin Choi
Travis Dick
Claudio Gentile
Andrés Munoz Medina
43
14
0
06 Feb 2023
The curse of overparametrization in adversarial training: Precise
  analysis of robust generalization for random features regression
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression
Hamed Hassani
Adel Javanmard
AAML
35
37
0
13 Jan 2022
An Overview of Privacy in Machine Learning
An Overview of Privacy in Machine Learning
Emiliano De Cristofaro
SILM
65
86
0
18 May 2020
Learning from Aggregate Observations
Learning from Aggregate Observations
Yivan Zhang
Nontawat Charoenphakdee
Zheng Wu
Masashi Sugiyama
65
28
0
14 Apr 2020
On the Complexity of Learning from Label Proportions
On the Complexity of Learning from Label Proportions
Benjamin Fish
L. Reyzin
26
16
0
07 Apr 2020
Precise Tradeoffs in Adversarial Training for Linear Regression
Precise Tradeoffs in Adversarial Training for Linear Regression
Adel Javanmard
Mahdi Soltanolkotabi
Hamed Hassani
AAML
58
109
0
24 Feb 2020
The generalization error of random features regression: Precise
  asymptotics and double descent curve
The generalization error of random features regression: Precise asymptotics and double descent curve
Song Mei
Andrea Montanari
99
639
0
14 Aug 2019
Learning Neural Networks with Adaptive Regularization
Learning Neural Networks with Adaptive Regularization
Han Zhao
Yao-Hung Hubert Tsai
Ruslan Salakhutdinov
Geoffrey J. Gordon
30
15
0
14 Jul 2019
Deep multi-class learning from label proportions
Deep multi-class learning from label proportions
Gabriel Dulac-Arnold
Neil Zeghidour
Marco Cuturi
Lucas Beyer
Jean-Philippe Vert
54
50
0
30 May 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Trevor Hastie
Andrea Montanari
Saharon Rosset
Robert Tibshirani
199
746
0
19 Mar 2019
On the Minimal Supervision for Training Any Binary Classifier from Only
  Unlabeled Data
On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data
Nan Lu
Gang Niu
A. Menon
Masashi Sugiyama
MQ
73
87
0
31 Aug 2018
Privacy Preserving Machine Learning: Threats and Solutions
Privacy Preserving Machine Learning: Threats and Solutions
Mohammad Al-Rubaie
Jerome Chang
60
337
0
27 Mar 2018
Co-training for Demographic Classification Using Deep Learning from
  Label Proportions
Co-training for Demographic Classification Using Deep Learning from Label Proportions
Ehsan Mohammady Ardehaly
A. Culotta
VLM
42
61
0
13 Sep 2017
Towards the Science of Security and Privacy in Machine Learning
Towards the Science of Security and Privacy in Machine Learning
Nicolas Papernot
Patrick McDaniel
Arunesh Sinha
Michael P. Wellman
AAML
89
474
0
11 Nov 2016
On Learning from Label Proportions
On Learning from Label Proportions
Felix X. Yu
Krzysztof Choromanski
Sanjiv Kumar
Tony Jebara
Shih-Fu Chang
88
84
0
24 Feb 2014
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