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Doubly-stochastic mining for heterogeneous retrieval

Doubly-stochastic mining for heterogeneous retrieval

23 April 2020
A. S. Rawat
A. Menon
Andreas Veit
Felix X. Yu
Sashank J. Reddi
Sanjiv Kumar
ArXivPDFHTML

Papers citing "Doubly-stochastic mining for heterogeneous retrieval"

17 / 17 papers shown
Title
Distributionally Robust Language Modeling
Distributionally Robust Language Modeling
Yonatan Oren
Shiori Sagawa
Tatsunori B. Hashimoto
Percy Liang
OOD
42
171
0
04 Sep 2019
Agnostic Federated Learning
Agnostic Federated Learning
M. Mohri
Gary Sivek
A. Suresh
FedML
64
928
0
01 Feb 2019
Fairness risk measures
Fairness risk measures
Robert C. Williamson
A. Menon
FaML
110
139
0
24 Jan 2019
A no-regret generalization of hierarchical softmax to extreme
  multi-label classification
A no-regret generalization of hierarchical softmax to extreme multi-label classification
Marek Wydmuch
Kalina Jasinska
Mikhail Kuznetsov
R. Busa-Fekete
Krzysztof Dembczyñski
100
101
0
27 Oct 2018
Learning Models with Uniform Performance via Distributionally Robust
  Optimization
Learning Models with Uniform Performance via Distributionally Robust Optimization
John C. Duchi
Hongseok Namkoong
OOD
39
413
0
20 Oct 2018
Stochastic Negative Mining for Learning with Large Output Spaces
Stochastic Negative Mining for Learning with Large Output Spaces
Sashank J. Reddi
Satyen Kale
Felix X. Yu
D. Holtmann-Rice
Jiecao Chen
Sanjiv Kumar
NoLa
33
62
0
16 Oct 2018
Fairness Without Demographics in Repeated Loss Minimization
Fairness Without Demographics in Repeated Loss Minimization
Tatsunori B. Hashimoto
Megha Srivastava
Hongseok Namkoong
Percy Liang
FaML
49
581
0
20 Jun 2018
Unleashing Linear Optimizers for Group-Fair Learning and Optimization
Unleashing Linear Optimizers for Group-Fair Learning and Optimization
Daniel Alabi
Nicole Immorlica
Adam Tauman Kalai
FedML
FaML
28
27
0
11 Apr 2018
Learning with Average Top-k Loss
Learning with Average Top-k Loss
Yanbo Fan
Siwei Lyu
Yiming Ying
Bao-Gang Hu
DML
103
103
0
24 May 2017
Efficient softmax approximation for GPUs
Efficient softmax approximation for GPUs
Edouard Grave
Armand Joulin
Moustapha Cissé
David Grangier
Hervé Jégou
55
271
0
14 Sep 2016
DiSMEC - Distributed Sparse Machines for Extreme Multi-label
  Classification
DiSMEC - Distributed Sparse Machines for Extreme Multi-label Classification
Rohit Babbar
Bernhard Schölkopf
33
252
0
08 Sep 2016
Minimizing the Maximal Loss: How and Why?
Minimizing the Maximal Loss: How and Why?
Shai Shalev-Shwartz
Y. Wexler
18
81
0
04 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.1K
192,638
0
10 Dec 2015
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Florian Schroff
Dmitry Kalenichenko
James Philbin
3DH
224
13,079
0
12 Mar 2015
On Using Very Large Target Vocabulary for Neural Machine Translation
On Using Very Large Target Vocabulary for Neural Machine Translation
Sébastien Jean
Kyunghyun Cho
Roland Memisevic
Yoshua Bengio
104
1,010
0
05 Dec 2014
Distributed Representations of Words and Phrases and their
  Compositionality
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov
Ilya Sutskever
Kai Chen
G. Corrado
J. Dean
NAI
OCL
237
33,445
0
16 Oct 2013
Large-scale Multi-label Learning with Missing Labels
Large-scale Multi-label Learning with Missing Labels
Hsiang-Fu Yu
Prateek Jain
Purushottam Kar
Inderjit S. Dhillon
MQ
60
492
0
18 Jul 2013
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