Zhu, Libin

1. Loss landscapes and optimization in over-parameterized non-linear systems and neural networks
   2020/02/29 by Chaoyue Liu, Liu, Chaoyue, Libin Zhu +3 · 21 citations
   Computer Science · Physics and Astronomy · Mathematics · #Stochastic Gradient Optimization Techniques #Model Reduction and Neural Networks #Markov Chains and Monte Carlo Methods
2. On the linearity of large non-linear models: when and why the tangent kernel is constant
   2020/10/02 by Chaoyue Liu, Libin Zhu, Liu, Chaoyue +3 · 9 citations
   Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Model Reduction and Neural Networks #Stochastic Gradient Optimization Techniques
3. Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning
   2023/06/07 by Libin Zhu, Zhu, Libin, Chaoyue Liu +5 · 1 voice · 3 citations
   Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Neural Networks and Applications #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques #cs.LG #math.OC #stat.ML
4. Iteratively reweighted kernel machines efficiently learn sparse functions
   2025/05/13 by Zhu, Libin, Davis, Damek, Drusvyatskiy, Dmitriy +1 · 5 citations
   #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Statistics Theory (math.ST)
5. Quadratic models for understanding catapult dynamics of neural networks
   2022/05/24 by Libin Zhu, Zhu, Libin, Chaoyue Liu +5 · 1 citation
   Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications #Optimization and Control (math.OC)
6. Restricted Strong Convexity of Deep Learning Models with Smooth Activations
   2022/09/29 by Arindam Banerjee, Pedro Cisneros‐Velarde, Banerjee, Arindam +5 · 1 citation
   Computer Science · Engineering · Medicine · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Medical Imaging Techniques and Applications #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
7. Emergence in non-neural models: grokking modular arithmetic via average gradient outer product
   2024/07/29 by Neil Mallinar, Daniel Beaglehole, Mallinar, Neil +9 · 2 citations
   Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications