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Surrogate Functions for Maximizing Precision at the Top

Surrogate Functions for Maximizing Precision at the Top

26 May 2015
Purushottam Kar
Harikrishna Narasimhan
Prateek Jain
ArXiv (abs)PDFHTML

Papers citing "Surrogate Functions for Maximizing Precision at the Top"

14 / 14 papers shown
Title
A Recommender System for Scientific Datasets and Analysis Pipelines
A Recommender System for Scientific Datasets and Analysis Pipelines
M. Mazaheri
Greg Kiar
Tristan Glatard
AI4TS
28
3
0
20 Aug 2021
Implicit Rate-Constrained Optimization of Non-decomposable Objectives
Implicit Rate-Constrained Optimization of Non-decomposable Objectives
Abhishek Kumar
Harikrishna Narasimhan
Andrew Cotter
87
10
0
23 Jul 2021
Label Disentanglement in Partition-based Extreme Multilabel
  Classification
Label Disentanglement in Partition-based Extreme Multilabel Classification
Xuanqing Liu
Wei-Cheng Chang
Hsiang-Fu Yu
Cho-Jui Hsieh
Inderjit S. Dhillon
61
11
0
24 Jun 2021
General Framework for Binary Classification on Top Samples
General Framework for Binary Classification on Top Samples
Lukáš Adam
V. Mácha
Václav Smídl
Tomás Pevný
47
5
0
25 Feb 2020
Optimizing Black-box Metrics with Adaptive Surrogates
Optimizing Black-box Metrics with Adaptive Surrogates
Qijia Jiang
Olaoluwa Adigun
Harikrishna Narasimhan
M. M. Fard
Maya R. Gupta
41
17
0
20 Feb 2020
Rich-Item Recommendations for Rich-Users: Exploiting Dynamic and Static
  Side Information
Rich-Item Recommendations for Rich-Users: Exploiting Dynamic and Static Side Information
A. Budhiraja
Gaurush Hiranandani
Darshak Chhatbar
Aditya Sinha
Navya Yarrabelly
Ayush Choure
Oluwasanmi Koyejo
Prateek Jain
58
4
0
28 Jan 2020
AP-Perf: Incorporating Generic Performance Metrics in Differentiable
  Learning
AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning
Rizal Fathony
J. Zico Kolter
FedML
49
15
0
02 Dec 2019
Efficient Algorithms for Smooth Minimax Optimization
Efficient Algorithms for Smooth Minimax Optimization
K. K. Thekumparampil
Prateek Jain
Praneeth Netrapalli
Sewoong Oh
103
191
0
02 Jul 2019
Backdrop: Stochastic Backpropagation
Backdrop: Stochastic Backpropagation
Siavash Golkar
Kyle Cranmer
45
2
0
04 Jun 2018
A plug-in approach to maximising precision at the top and recall at the
  top
A plug-in approach to maximising precision at the top and recall at the top
Dirk Tasche
41
7
0
09 Apr 2018
Constrained Classification and Ranking via Quantiles
Constrained Classification and Ranking via Quantiles
Alan Mackey
Xiyang Luo
Elad Eban
47
6
0
28 Feb 2018
Optimizing Non-decomposable Measures with Deep Networks
Optimizing Non-decomposable Measures with Deep Networks
Amartya Sanyal
Pawan Kumar
Purushottam Kar
Sanjay Chawla
Fabrizio Sebastiani
47
26
0
31 Jan 2018
Online Optimization Methods for the Quantification Problem
Online Optimization Methods for the Quantification Problem
Purushottam Kar
Shuai Li
Harikrishna Narasimhan
Sanjay Chawla
Fabrizio Sebastiani
39
46
0
13 May 2016
Transductive Optimization of Top k Precision
Transductive Optimization of Top k Precision
Li-Ping Liu
Thomas G. Dietterich
Nan Li
Zhi Zhou
64
17
0
20 Oct 2015
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