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Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised
  Algorithm
v1v2v3 (latest)

Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm

Journal of Artificial Intelligence Research (JAIR), 2016
2 July 2016
Yury Maximov
Massih-Reza Amini
Zaïd Harchaoui
ArXiv (abs)PDFHTML

Papers citing "Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm"

15 / 15 papers shown
FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness
  for Semi-Supervised Learning
FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised LearningNeural Information Processing Systems (NeurIPS), 2023
Zhuo Huang
Li Shen
Jun-chen Yu
Bo Han
Tongliang Liu
FedML
264
35
0
25 Oct 2023
Long-term drought prediction using deep neural networks based on
  geospatial weather data
Long-term drought prediction using deep neural networks based on geospatial weather dataEnvironmental Modelling & Software (Environ. Model. Softw.), 2023
Alexander Marusov
Vsevolod Grabar
Yury Maximov
Nazar Sotiriadi
Alexander Bulkin
Alexey Zaytsev
285
19
0
12 Sep 2023
Unsupervised Domain Adaptation with Deep Neural-Network
Unsupervised Domain Adaptation with Deep Neural-Network
Artem Bituitskii
OOD
266
0
0
10 Jul 2023
Deep Learning with Partially Labeled Data for Radio Map Reconstruction
Deep Learning with Partially Labeled Data for Radio Map Reconstruction
Alkesandra Malkova
Massih-Reza Amini
B. Denis
C. Villien
191
0
0
07 Jun 2023
DRIFT: A Federated Recommender System with Implicit Feedback on the
  Items
DRIFT: A Federated Recommender System with Implicit Feedback on the Items
Theo Nommay
FedML
91
0
0
17 Apr 2023
Inference and Optimization for Engineering and Physical Systems
Inference and Optimization for Engineering and Physical Systems
M. Krechetov
142
0
0
29 Aug 2022
Multi-class Classification with Fuzzy-feature Observations: Theory and
  Algorithms
Multi-class Classification with Fuzzy-feature Observations: Theory and AlgorithmsIEEE Transactions on Cybernetics (IEEE Trans. Cybern.), 2022
Guangzhi Ma
Jie Lu
Yifan Zhang
Zhen Fang
Guangquan Zhang
198
8
0
09 Jun 2022
Self-Training: A Survey
Self-Training: A SurveyNeurocomputing (Neurocomputing), 2022
Massih-Reza Amini
Vasilii Feofanov
Loïc Pauletto
Lies Hadjadj
Emilie Devijver
Yury Maximov
SSL
551
152
0
24 Feb 2022
Self-Training of Halfspaces with Generalization Guarantees under Massart
  Mislabeling Noise Model
Self-Training of Halfspaces with Generalization Guarantees under Massart Mislabeling Noise Model
Lies Hadjadj
Massih-Reza Amini
Sana Louhichi
A. Deschamps
274
1
0
29 Nov 2021
Multi-class Probabilistic Bounds for Self-learning
Multi-class Probabilistic Bounds for Self-learning
Vasilii Feofanov
Emilie Devijver
Massih-Reza Amini
171
3
0
29 Sep 2021
Fine-grained Generalization Analysis of Structured Output Prediction
Fine-grained Generalization Analysis of Structured Output PredictionInternational Joint Conference on Artificial Intelligence (IJCAI), 2021
Waleed Mustafa
Yunwen Lei
Antoine Ledent
Matthias Kirchler
227
10
0
31 May 2021
Fine-grained Generalization Analysis of Vector-valued Learning
Fine-grained Generalization Analysis of Vector-valued LearningAAAI Conference on Artificial Intelligence (AAAI), 2021
Liang Wu
Antoine Ledent
Yunwen Lei
Matthias Kirchler
178
11
0
29 Apr 2021
Multiclass classification by sparse multinomial logistic regression
Multiclass classification by sparse multinomial logistic regressionIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
F. Abramovich
V. Grinshtein
Tomer Levy
211
31
0
04 Mar 2020
Semi-supervised Vector-valued Learning: Improved Bounds and Algorithms
Semi-supervised Vector-valued Learning: Improved Bounds and AlgorithmsPattern Recognition (Pattern Recognit.), 2019
Jian Li
Yong Liu
Weiping Wang
270
3
0
11 Sep 2019
Improvability Through Semi-Supervised Learning: A Survey of Theoretical
  Results
Improvability Through Semi-Supervised Learning: A Survey of Theoretical Results
A. Mey
Marco Loog
SSL
249
20
0
26 Aug 2019
1
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