ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1905.13587
  4. Cited By
GENO -- GENeric Optimization for Classical Machine Learning

GENO -- GENeric Optimization for Classical Machine Learning

31 May 2019
Soren Laue
Matthias Mitterreiter
Joachim Giesen
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "GENO -- GENeric Optimization for Classical Machine Learning"

10 / 10 papers shown
Title
Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization
Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization
Zhihui Zhu
Xiao Li
Kai Liu
Qiuwei Li
33
46
0
14 Nov 2018
TensorFlow: A system for large-scale machine learning
TensorFlow: A system for large-scale machine learning
Martín Abadi
P. Barham
Jianmin Chen
Zhiwen Chen
Andy Davis
...
Vijay Vasudevan
Pete Warden
Martin Wicke
Yuan Yu
Xiaoqiang Zhang
GNNAI4CE
435
18,361
0
27 May 2016
A Simple Practical Accelerated Method for Finite Sums
A Simple Practical Accelerated Method for Finite Sums
Aaron Defazio
145
121
0
08 Feb 2016
MLlib: Machine Learning in Apache Spark
MLlib: Machine Learning in Apache Spark
Xiangrui Meng
Joseph K. Bradley
Burak Yavuz
Evan R. Sparks
Shivaram Venkataraman
...
Reynold Xin
Michael Franklin
R. Zadeh
Matei A. Zaharia
Ameet Talwalkar
62
1,786
0
26 May 2015
Proximal Algorithms in Statistics and Machine Learning
Proximal Algorithms in Statistics and Machine Learning
Nicholas G. Polson
James G. Scott
Brandon T. Willard
323
150
0
11 Feb 2015
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly
  Convex Composite Objectives
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives
Aaron Defazio
Francis R. Bach
Simon Lacoste-Julien
ODL
139
1,830
0
01 Jul 2014
Caffe: Convolutional Architecture for Fast Feature Embedding
Caffe: Convolutional Architecture for Fast Feature Embedding
Yangqing Jia
Evan Shelhamer
Jeff Donahue
Sergey Karayev
Jonathan Long
Ross B. Girshick
S. Guadarrama
Trevor Darrell
VLMBDL3DV
296
14,715
0
20 Jun 2014
Probabilistic Latent Semantic Analysis
Probabilistic Latent Semantic Analysis
Thomas Hofmann
449
2,808
0
23 Jan 2013
Stochastic Dual Coordinate Ascent Methods for Regularized Loss
  Minimization
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
Shai Shalev-Shwartz
Tong Zhang
198
1,033
0
10 Sep 2012
Runtime Guarantees for Regression Problems
Runtime Guarantees for Regression Problems
Hui Han Chin
Aleksander Madry
Gary Miller
Richard Peng
66
54
0
06 Oct 2011
1