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Robust Learning of Fixed-Structure Bayesian Networks
v1v2 (latest)

Robust Learning of Fixed-Structure Bayesian Networks

Neural Information Processing Systems (NeurIPS), 2016
23 June 2016
Yu Cheng
Ilias Diakonikolas
D. Kane
Alistair Stewart
    OOD
ArXiv (abs)PDFHTML

Papers citing "Robust Learning of Fixed-Structure Bayesian Networks"

32 / 32 papers shown
Title
MBGDT:Robust Mini-Batch Gradient Descent
MBGDT:Robust Mini-Batch Gradient Descent
Hanming Wang
Haozheng Luo
Yue Wang
83
5
0
14 Jun 2022
Streaming Algorithms for High-Dimensional Robust Statistics
Streaming Algorithms for High-Dimensional Robust StatisticsInternational Conference on Machine Learning (ICML), 2022
Ilias Diakonikolas
D. Kane
Ankit Pensia
Thanasis Pittas
203
22
0
26 Apr 2022
Robust Estimation for Random Graphs
Robust Estimation for Random GraphsAnnual Conference Computational Learning Theory (COLT), 2021
Jayadev Acharya
Ayush Jain
Gautam Kamath
A. Suresh
Huanyu Zhang
183
9
0
09 Nov 2021
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean
  Estimation
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation
Ilias Diakonikolas
D. Kane
Daniel Kongsgaard
Haibin Zhang
Kevin Tian
FedML
160
22
0
16 Jun 2021
Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear
  Time
Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear TimeInternational Conference on Learning Representations (ICLR), 2021
Yu Cheng
Honghao Lin
OOD
117
0
0
12 May 2021
Outlier-Robust Learning of Ising Models Under Dobrushin's Condition
Outlier-Robust Learning of Ising Models Under Dobrushin's ConditionAnnual Conference Computational Learning Theory (COLT), 2021
Ilias Diakonikolas
D. Kane
Alistair Stewart
Yuxin Sun
146
18
0
03 Feb 2021
SGA: A Robust Algorithm for Partial Recovery of Tree-Structured
  Graphical Models with Noisy Samples
SGA: A Robust Algorithm for Partial Recovery of Tree-Structured Graphical Models with Noisy SamplesInternational Conference on Machine Learning (ICML), 2021
Anshoo Tandon
Aldric H. J. Yuan
Vincent Y. F. Tan
126
9
0
22 Jan 2021
Robustly Learning Mixtures of $k$ Arbitrary Gaussians
Robustly Learning Mixtures of kkk Arbitrary GaussiansSymposium on the Theory of Computing (STOC), 2020
Ainesh Bakshi
Ilias Diakonikolas
Hengrui Jia
D. Kane
Pravesh Kothari
Santosh Vempala
270
72
0
03 Dec 2020
The FEDHC Bayesian network learning algorithm
The FEDHC Bayesian network learning algorithm
M. Tsagris
194
4
0
30 Nov 2020
List-Decodable Mean Estimation in Nearly-PCA Time
List-Decodable Mean Estimation in Nearly-PCA TimeNeural Information Processing Systems (NeurIPS), 2020
Ilias Diakonikolas
D. Kane
Daniel Kongsgaard
Haibin Zhang
Kevin Tian
143
17
0
19 Nov 2020
Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers
Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers
Lunjia Hu
Omer Reingold
OOD
322
7
0
18 Aug 2020
List-Decodable Mean Estimation via Iterative Multi-Filtering
List-Decodable Mean Estimation via Iterative Multi-Filtering
Ilias Diakonikolas
D. Kane
Daniel Kongsgaard
111
24
0
18 Jun 2020
Robustly Learning any Clusterable Mixture of Gaussians
Robustly Learning any Clusterable Mixture of Gaussians
Ilias Diakonikolas
Samuel B. Hopkins
D. Kane
Sushrut Karmalkar
143
47
0
13 May 2020
Exact Asymptotics for Learning Tree-Structured Graphical Models with
  Side Information: Noiseless and Noisy Samples
Exact Asymptotics for Learning Tree-Structured Graphical Models with Side Information: Noiseless and Noisy Samples
Anshoo Tandon
Vincent Y. F. Tan
Shiyao Zhu
113
7
0
09 May 2020
Outlier-Robust High-Dimensional Sparse Estimation via Iterative
  Filtering
Outlier-Robust High-Dimensional Sparse Estimation via Iterative FilteringNeural Information Processing Systems (NeurIPS), 2019
Ilias Diakonikolas
Sushrut Karmalkar
D. Kane
Eric Price
Alistair Stewart
78
41
0
19 Nov 2019
Recent Advances in Algorithmic High-Dimensional Robust Statistics
Recent Advances in Algorithmic High-Dimensional Robust Statistics
Ilias Diakonikolas
D. Kane
OOD
193
192
0
14 Nov 2019
Faster Algorithms for High-Dimensional Robust Covariance Estimation
Faster Algorithms for High-Dimensional Robust Covariance EstimationAnnual Conference Computational Learning Theory (COLT), 2019
Yu Cheng
Ilias Diakonikolas
Rong Ge
David P. Woodruff
125
67
0
11 Jun 2019
How Hard Is Robust Mean Estimation?
How Hard Is Robust Mean Estimation?Annual Conference Computational Learning Theory (COLT), 2019
Samuel B. Hopkins
Jerry Li
119
38
0
19 Mar 2019
On resampling vs. adjusting probabilistic graphical models in estimation
  of distribution algorithms
On resampling vs. adjusting probabilistic graphical models in estimation of distribution algorithms
Mohamed El Yafrani
M. Martins
M. Delgado
Inkyung Sung
R. Lüders
Markus Wagner
TPM
89
0
0
15 Feb 2019
High-Dimensional Robust Mean Estimation in Nearly-Linear Time
High-Dimensional Robust Mean Estimation in Nearly-Linear TimeACM-SIAM Symposium on Discrete Algorithms (SODA), 2018
Yu Cheng
Ilias Diakonikolas
Rong Ge
113
126
0
23 Nov 2018
Deep Neural Network Concepts for Background Subtraction: A Systematic
  Review and Comparative Evaluation
Deep Neural Network Concepts for Background Subtraction: A Systematic Review and Comparative Evaluation
T. Bouwmans
S. Javed
M. Sultana
Soon Ki Jung
127
324
0
13 Nov 2018
Robust Estimation and Generative Adversarial Nets
Robust Estimation and Generative Adversarial Nets
Chao Gao
Jiyi Liu
Yuan Yao
Weizhi Zhu
226
29
0
04 Oct 2018
Efficient Algorithms and Lower Bounds for Robust Linear Regression
Efficient Algorithms and Lower Bounds for Robust Linear Regression
Ilias Diakonikolas
Weihao Kong
Alistair Stewart
175
166
0
31 May 2018
Sever: A Robust Meta-Algorithm for Stochastic Optimization
Sever: A Robust Meta-Algorithm for Stochastic Optimization
Ilias Diakonikolas
Gautam Kamath
D. Kane
Jerry Li
Jacob Steinhardt
Alistair Stewart
155
302
0
07 Mar 2018
List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical
  Gaussians
List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians
Ilias Diakonikolas
D. Kane
Alistair Stewart
192
150
0
20 Nov 2017
Learning Geometric Concepts with Nasty Noise
Learning Geometric Concepts with Nasty Noise
Ilias Diakonikolas
D. Kane
Alistair Stewart
AAML
147
92
0
05 Jul 2017
Robustly Learning a Gaussian: Getting Optimal Error, Efficiently
Robustly Learning a Gaussian: Getting Optimal Error, Efficiently
Ilias Diakonikolas
Gautam Kamath
D. Kane
Jerry Li
Ankur Moitra
Alistair Stewart
158
139
0
12 Apr 2017
Resilience: A Criterion for Learning in the Presence of Arbitrary
  Outliers
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers
Jacob Steinhardt
Moses Charikar
Gregory Valiant
239
142
0
15 Mar 2017
Being Robust (in High Dimensions) Can Be Practical
Being Robust (in High Dimensions) Can Be Practical
Ilias Diakonikolas
Gautam Kamath
D. Kane
Jerry Li
Ankur Moitra
Alistair Stewart
264
264
0
02 Mar 2017
Robust Sparse Estimation Tasks in High Dimensions
Robust Sparse Estimation Tasks in High Dimensions
Jerry Li
193
27
0
20 Feb 2017
Testing Bayesian Networks
Testing Bayesian Networks
C. Canonne
Ilias Diakonikolas
D. Kane
Alistair Stewart
TPM
169
74
0
09 Dec 2016
Statistical Query Lower Bounds for Robust Estimation of High-dimensional
  Gaussians and Gaussian Mixtures
Statistical Query Lower Bounds for Robust Estimation of High-dimensional Gaussians and Gaussian Mixtures
Ilias Diakonikolas
D. Kane
Alistair Stewart
161
241
0
10 Nov 2016
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