Long, Philip M.

1. The Singular Values of Convolutional Layers
   2018/05/26 by Hanie Sedghi, Vineet Gupta, Sedghi, Hanie +3 · 8 citations
   Computer Science · Engineering · Physics and Astronomy · #Advanced Numerical Analysis Techniques #Artificial Intelligence (cs.AI) #Electromagnetic Scattering and Analysis #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms
2. The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima
   2022/10/04 by Bartlett, Peter L., Long, Philip M., Bousquet, Olivier · 8 citations
   #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
3. Active and passive learning of linear separators under log-concave distributions
   2012/11/06 by Maria Florina Balcan, Philip M. Long, Balcan, Maria Florina +1 · 3 citations
   Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Mineral Processing and Grinding #Neural Networks and Applications #Statistics Theory (math.ST)
4. Generalization bounds for deep convolutional neural networks
   2019/05/29 by Philip M. Long, Hanie Sedghi, Long, Philip M. +1 · 3 citations
   Computer Science · #Advanced Neural Network Applications #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Neural and Evolutionary Computing (cs.NE) #Statistics Theory (math.ST)
5. Gradient descent with identity initialization efficiently learns\n positive definite linear transformations by deep residual networks
   2018/02/16 by Peter L. Bartlett, David P. Helmbold, Bartlett, Peter L. +3 · 2 citations
   Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Neural and Evolutionary Computing (cs.NE) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST) #Stochastic Gradient Optimization Techniques
6. Finite-sample Analysis of Interpolating Linear Classifiers in the Overparameterized Regime
   2020/04/25 by Niladri S. Chatterji, Philip M. Long, Chatterji, Niladri S. +1 · 2 citations
   Computer Science · #Machine Learning and Algorithms #Machine Learning and Data Classification #Imbalanced Data Classification Techniques
7. The Interplay Between Implicit Bias and Benign Overfitting in Two-Layer Linear Networks
   2021/08/25 by Chatterji, Niladri S., Long, Philip M., Bartlett, Peter L. · 2 citations
   #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
8. Sharpness-Aware Minimization and the Edge of Stability
   2023/09/21 by Long, Philip M., Bartlett, Peter L. · 3 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE)
9. Oracle Lower Bounds for Stochastic Gradient Sampling Algorithms
   2020/02/01 by Chatterji, Niladri S., Bartlett, Peter L., Long, Philip M. · 1 citation
   #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
10. On the Global Convergence of Training Deep Linear ResNets
    2020/03/02 by Zou, Difan, Long, Philip M., Gu, Quanquan · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
11. Foolish Crowds Support Benign Overfitting
    2021/10/06 by Niladri S. Chatterji, Chatterji, Niladri S., Philip M. Long +1 · 2 citations
    Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Statistics Theory (math.ST)
12. Properties of the After Kernel
    2021/05/21 by Philip M. Long, Long, Philip M. · 1 citation
    Computer Science · #Stochastic Gradient Optimization Techniques #Advanced Neural Network Applications #Neural Networks and Applications
13. Deep Linear Networks can Benignly Overfit when Shallow Ones Do
    2022/09/19 by Chatterji, Niladri S., Long, Philip M. · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)