引用次数
引用: 26,625
H-指数: 49
I10-指数 : 72
出版物: 110
JHelioviewer: Exploring Petabytes of Solar Images
Keith Hughitt , George Dimitoglou , Ludwig Schmidt , Bernhard Fleck
38th COSPAR Scientific Assembly 38 8
2010
Fast Algorithms for Structured Sparsity
Piotr Indyk , Chinmay Hegde , Ludwig Schmidt
Bulletin of The European Association for Theoretical Computer Science 3 ( 117)
20
2015
A Nearly-Linear Time Framework for Graph-Structured Sparsity
Piotr Indyk , Chinmay Hegde , Ludwig Schmidt
international conference on machine learning 928 -937
59
2015
Practical and optimal LSH for angular distance
Piotr Indyk , Ludwig Schmidt , Alexandr Andoni , Thijs Laarhoven
neural information processing systems 28 1225 -1233
156
2015
Fast recovery from a union of subspaces
Piotr Indyk , Chinmay Hegde , Ludwig Schmidt
neural information processing systems 29 4394 -4402
12
2016
Better approximations for tree sparsity in nearly-linear time
Piotr Indyk , Arturs Backurs , Ludwig Schmidt
symposium on discrete algorithms 2215 -2229
22
2017
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks
Piotr Indyk , Arturs Backurs , Ludwig Schmidt
neural information processing systems 30 4308 -4318
14
2017
Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities
Ludwig Schmidt , Jerry Li
conference on learning theory 1302 -1382
18
2017
Communication-Efficient Distributed Learning of Discrete Distributions
Ilias Diakonikolas , Krzysztof Onak , Elena Grigorescu , Ludwig Schmidt
neural information processing systems 30 6391 -6401
20
2017
Learning Representations for Faster Similarity Search
Kunal Talwar , Ludwig Schmidt
2018
Model Reconstruction from Model Explanations
Anca D. Dragan , Ludwig Schmidt , Moritz Hardt , Smitha Milli
arXiv: Machine Learning
115
2018
On the Limitations of First-Order Approximation in GAN Dynamics
Ludwig Schmidt , Aleksander Madry , Jerry Li , John Peebles
arXiv: Learning
45
2017
Do ImageNet Classifiers Generalize to ImageNet
Benjamin Recht , Vaishaal Shankar , Ludwig Schmidt , Rebecca Roelofs
arXiv: Computer Vision and Pattern Recognition
838
2019
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians
Ludwig Schmidt , Aleksander Madry , Slobodan Mitrovic
international conference on artificial intelligence and statistics 20 -28
1
2018
Adversarially Robust Generalization Requires More Data
Kunal Talwar , Ludwig Schmidt , Aleksander Madry , Dimitris Tsipras
neural information processing systems 31 5014 -5026
249
2018
Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms
Ilias Diakonikolas , Ludwig Schmidt , Jerry Li
conference on learning theory 819 -842
7
2018
A Classification-Based Study of Covariate Shift in GAN Distributions
Ludwig Schmidt , Aleksander Madry , Shibani Santurkar
international conference on machine learning 4480 -4489
57
2018
Towards Deep Learning Models Resistant to Adversarial Attacks.
Adrian Vladu , Ludwig Schmidt , Dimitris Tsipras , Aleksandar Makelov
international conference on learning representations
7
2018
Fast algorithms for segmented regression
Ilias Diakonikolas , Jayadev Acharya , Ludwig Schmidt , Jerry Li
international conference on machine learning 2878 -2886
8
2016
Sample-optimal density estimation in nearly-linear time
Ilias Diakonikolas , Jayadev Acharya , Ludwig Schmidt , Jerry Li
symposium on discrete algorithms 1278 -1289
39
2017