#regularized — Public Fediverse posts

'Learning with a linear loss function: excess risk and estimation bound..."', by Guillaume Lecué, Lucie Neirac.

http://jmlr.org/papers/v25/23-1405.html

#adversarial #estimators #regularized

'Learning with a linear loss function: excess risk and estimation bound..."', by Guillaume Lecué, Lucie Neirac.

http://jmlr.org/papers/v25/23-1405.html

#adversarial #estimators #regularized

'Learning with a linear loss function: excess risk and estimation bound..."', by Guillaume Lecué, Lucie Neirac.

http://jmlr.org/papers/v25/23-1405.html

#adversarial #estimators #regularized

'Learning with a linear loss function: excess risk and estimation bound..."', by Guillaume Lecué, Lucie Neirac.

http://jmlr.org/papers/v25/23-1405.html

#adversarial #estimators #regularized

'Learning with a linear loss function: excess risk and estimation bound..."', by Guillaume Lecué, Lucie Neirac.

http://jmlr.org/papers/v25/23-1405.html

#adversarial #estimators #regularized

'Accelerating Nuclear-norm Regularized Low-rank Matrix Optimization Through Burer-Monteiro Decomposition', by Ching-pei Lee, Ling Liang, Tianyun Tang, Kim-Chuan Toh.

http://jmlr.org/papers/v25/23-0049.html

#regularized #optimization #rank

'Accelerating Nuclear-norm Regularized Low-rank Matrix Optimization Through Burer-Monteiro Decomposition', by Ching-pei Lee, Ling Liang, Tianyun Tang, Kim-Chuan Toh.

http://jmlr.org/papers/v25/23-0049.html

#regularized #optimization #rank

'Accelerating Nuclear-norm Regularized Low-rank Matrix Optimization Through Burer-Monteiro Decomposition', by Ching-pei Lee, Ling Liang, Tianyun Tang, Kim-Chuan Toh.

http://jmlr.org/papers/v25/23-0049.html

#regularized #optimization #rank

'Accelerating Nuclear-norm Regularized Low-rank Matrix Optimization Through Burer-Monteiro Decomposition', by Ching-pei Lee, Ling Liang, Tianyun Tang, Kim-Chuan Toh.

http://jmlr.org/papers/v25/23-0049.html

#regularized #optimization #rank

'An Inexact Projected Regularized Newton Method for Fused Zero-norms Regularization Problems', by Yuqia Wu, Shaohua Pan, Xiaoqi Yang.

http://jmlr.org/papers/v25/23-1700.html

#regularization #regularized #gradient

'An Inexact Projected Regularized Newton Method for Fused Zero-norms Regularization Problems', by Yuqia Wu, Shaohua Pan, Xiaoqi Yang.

http://jmlr.org/papers/v25/23-1700.html

#regularization #regularized #gradient

'An Inexact Projected Regularized Newton Method for Fused Zero-norms Regularization Problems', by Yuqia Wu, Shaohua Pan, Xiaoqi Yang.

http://jmlr.org/papers/v25/23-1700.html

#regularization #regularized #gradient

'An Inexact Projected Regularized Newton Method for Fused Zero-norms Regularization Problems', by Yuqia Wu, Shaohua Pan, Xiaoqi Yang.

http://jmlr.org/papers/v25/23-1700.html

#regularization #regularized #gradient

'Debiasing Evaluations That Are Biased by Evaluations', by Jingyan Wang, Ivan Stelmakh, Yuting Wei, Nihar Shah.

http://jmlr.org/papers/v25/22-0775.html

#biases #bias #regularized

'Debiasing Evaluations That Are Biased by Evaluations', by Jingyan Wang, Ivan Stelmakh, Yuting Wei, Nihar Shah.

http://jmlr.org/papers/v25/22-0775.html

#biases #bias #regularized

'Debiasing Evaluations That Are Biased by Evaluations', by Jingyan Wang, Ivan Stelmakh, Yuting Wei, Nihar Shah.

http://jmlr.org/papers/v25/22-0775.html

#biases #bias #regularized

'Debiasing Evaluations That Are Biased by Evaluations', by Jingyan Wang, Ivan Stelmakh, Yuting Wei, Nihar Shah.

http://jmlr.org/papers/v25/22-0775.html

#biases #bias #regularized

'Spectral Regularized Kernel Goodness-of-Fit Tests', by Omar Hagrass, Bharath K. Sriperumbudur, Bing Li.

http://jmlr.org/papers/v25/23-1031.html

#regularization #regularized #spectral

'Spectral Regularized Kernel Goodness-of-Fit Tests', by Omar Hagrass, Bharath K. Sriperumbudur, Bing Li.

http://jmlr.org/papers/v25/23-1031.html

#regularization #regularized #spectral

'Spectral Regularized Kernel Goodness-of-Fit Tests', by Omar Hagrass, Bharath K. Sriperumbudur, Bing Li.

http://jmlr.org/papers/v25/23-1031.html

#regularization #regularized #spectral

'Spectral Regularized Kernel Goodness-of-Fit Tests', by Omar Hagrass, Bharath K. Sriperumbudur, Bing Li.

http://jmlr.org/papers/v25/23-1031.html

#regularization #regularized #spectral

'Stochastic Regularized Majorization-Minimization with weakly convex and multi-convex surrogates', by Hanbaek Lyu.

http://jmlr.org/papers/v25/23-0349.html

#regularization #regularized #minimization

'Stochastic Regularized Majorization-Minimization with weakly convex and multi-convex surrogates', by Hanbaek Lyu.

http://jmlr.org/papers/v25/23-0349.html

#regularization #regularized #minimization

'Stochastic Regularized Majorization-Minimization with weakly convex and multi-convex surrogates', by Hanbaek Lyu.

http://jmlr.org/papers/v25/23-0349.html

#regularization #regularized #minimization

'Stochastic Regularized Majorization-Minimization with weakly convex and multi-convex surrogates', by Hanbaek Lyu.

http://jmlr.org/papers/v25/23-0349.html

#regularization #regularized #minimization

'Stochastic Regularized Majorization-Minimization with weakly convex and multi-convex surrogates', by Hanbaek Lyu.

http://jmlr.org/papers/v25/23-0349.html

#regularization #regularized #minimization

'On Regularized Radon-Nikodym Differentiation', by Duc Hoan Nguyen, Werner Zellinger, Sergei Pereverzyev.

http://jmlr.org/papers/v25/23-0567.html

#regularization #regularized #estimation

'On Regularized Radon-Nikodym Differentiation', by Duc Hoan Nguyen, Werner Zellinger, Sergei Pereverzyev.

http://jmlr.org/papers/v25/23-0567.html

#regularization #regularized #estimation

'On Regularized Radon-Nikodym Differentiation', by Duc Hoan Nguyen, Werner Zellinger, Sergei Pereverzyev.

http://jmlr.org/papers/v25/23-0567.html

#regularization #regularized #estimation

'On Regularized Radon-Nikodym Differentiation', by Duc Hoan Nguyen, Werner Zellinger, Sergei Pereverzyev.

http://jmlr.org/papers/v25/23-0567.html

#regularization #regularized #estimation

'Statistical analysis for a penalized EM algorithm in high-dimensional mixture linear regression model', by Ning Wang, Xin Zhang, Qing Mai.

http://jmlr.org/papers/v25/23-0296.html

#lasso #regularized #penalized

'Statistical analysis for a penalized EM algorithm in high-dimensional mixture linear regression model', by Ning Wang, Xin Zhang, Qing Mai.

http://jmlr.org/papers/v25/23-0296.html

#lasso #regularized #penalized

'Statistical analysis for a penalized EM algorithm in high-dimensional mixture linear regression model', by Ning Wang, Xin Zhang, Qing Mai.

http://jmlr.org/papers/v25/23-0296.html

#lasso #regularized #penalized

'Statistical analysis for a penalized EM algorithm in high-dimensional mixture linear regression model', by Ning Wang, Xin Zhang, Qing Mai.

http://jmlr.org/papers/v25/23-0296.html

#lasso #regularized #penalized

'On the Connection between Lp- and Risk Consistency and its Implications on Regularized Kernel Methods', by Hannes Köhler.

http://jmlr.org/papers/v25/23-0397.html

#regularized #kernel #risk

'On the Connection between Lp- and Risk Consistency and its Implications on Regularized Kernel Methods', by Hannes Köhler.

http://jmlr.org/papers/v25/23-0397.html

#regularized #kernel #risk

'On the Connection between Lp- and Risk Consistency and its Implications on Regularized Kernel Methods', by Hannes Köhler.

http://jmlr.org/papers/v25/23-0397.html

#regularized #kernel #risk

'On the Connection between Lp- and Risk Consistency and its Implications on Regularized Kernel Methods', by Hannes Köhler.

http://jmlr.org/papers/v25/23-0397.html

#regularized #kernel #risk

'Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces', by Rui Wang, Yuesheng Xu, Mingsong Yan.

http://jmlr.org/papers/v25/23-0645.html

#regularization #sparse #regularized

'Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces', by Rui Wang, Yuesheng Xu, Mingsong Yan.

http://jmlr.org/papers/v25/23-0645.html

#regularization #sparse #regularized

'Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces', by Rui Wang, Yuesheng Xu, Mingsong Yan.

http://jmlr.org/papers/v25/23-0645.html

#regularization #sparse #regularized

'Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces', by Rui Wang, Yuesheng Xu, Mingsong Yan.

http://jmlr.org/papers/v25/23-0645.html

#regularization #sparse #regularized

'Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization', by Shicong Cen, Yuting Wei, Yuejie Chi.

http://jmlr.org/papers/v25/21-1205.html

#regularization #reinforcement #regularized

'Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization', by Shicong Cen, Yuting Wei, Yuejie Chi.

http://jmlr.org/papers/v25/21-1205.html

#regularization #reinforcement #regularized

'Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization', by Shicong Cen, Yuting Wei, Yuejie Chi.

http://jmlr.org/papers/v25/21-1205.html

#regularization #reinforcement #regularized

'Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization', by Shicong Cen, Yuting Wei, Yuejie Chi.

http://jmlr.org/papers/v25/21-1205.html

#regularization #reinforcement #regularized

Attentional-Biased Stochastic Gradient Descent

Qi Qi, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang

Action editor: Changyou Chen.

https://openreview.net/forum?id=B0WYWvVA2r

#regularization #regularized #sgd

Attentional-Biased Stochastic Gradient Descent

Qi Qi, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang

Action editor: Changyou Chen.

https://openreview.net/forum?id=B0WYWvVA2r

#regularization #regularized #sgd

Attentional-Biased Stochastic Gradient Descent

Qi Qi, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang

Action editor: Changyou Chen.

https://openreview.net/forum?id=B0WYWvVA2r

#regularization #regularized #sgd

Attentional-Biased Stochastic Gradient Descent

Qi Qi, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang

Action editor: Changyou Chen.

https://openreview.net/forum?id=B0WYWvVA2r

#regularization #regularized #sgd