Nathan Srebro
- Equality of Opportunity in Supervised Learning
2016/10/07 by Moritz Hardt, Eric Price, Hardt, Moritz +3 · 396 citations
Social Sciences · Computer Science · #Ethics and Social Impacts of AI #Privacy-Preserving Technologies in Data #Explainable Artificial Intelligence (XAI)
- Exploring Generalization in Deep Learning
2017/06/27 by Behnam Neyshabur, Srinadh Bhojanapalli, Neyshabur, Behnam +5 · 53 citations
Computer Science · #Adversarial Robustness in Machine Learning #Neural Networks and Applications #Anomaly Detection Techniques and Applications
- Norm-Based Capacity Control in Neural Networks
2015/02/27 by Behnam Neyshabur, Neyshabur, Behnam, Ryota Tomioka +3 · 34 citations
Computer Science · Engineering · #Advanced Memory and Neural Computing #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE)
- Lower Bounds for Non-Convex Stochastic Optimization
2019/12/05 by Yossi Arjevani, Yair Carmon, Arjevani, Yossi +9 · 38 citations
Computer Science · Mathematics · Engineering · #Stochastic Gradient Optimization Techniques #Markov Chains and Monte Carlo Methods #Sparse and Compressive Sensing Techniques
- In Search of the Real Inductive Bias: On the Role of Implicit\n Regularization in Deep Learning
2014/12/20 by Behnam Neyshabur, Ryota Tomioka, Neyshabur, Behnam +3 · 27 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
- A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks
2017/07/29 by Behnam Neyshabur, Srinadh Bhojanapalli, Neyshabur, Behnam +3 · 24 citations
Computer Science · Engineering · #Advanced Neural Network Applications #FOS: Computer and information sciences #Fault Detection and Control Systems #Machine Learning (cs.LG) #Neural Networks and Applications
- Implicit Bias of Gradient Descent on Linear Convolutional Networks
2018/06/01 by Suriya Gunasekar, Gunasekar, Suriya, Jason D. Lee +5 · 22 citations
Computer Science · Engineering · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Stochastic Gradient Descent, Weighted Sampling, and the Randomized\n Kaczmarz algorithm
2013/10/21 by Deanna Needell, Nathan Srebro, Needell, Deanna +3 · 18 citations
Computer Science · Engineering · Mathematics · #52A99 #60G99 #62L20 #65B99 #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Numerical Analysis (math.NA) #Optimization and Control (math.OC) #Point processes and geometric inequalities #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Optimistic Rates for Learning with a Smooth Loss
2010/09/20 by Nathan Srebro, Srebro, Nathan, Karthik Sridharan +3 · 10 citations
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques
- Global Optimality of Local Search for Low Rank Matrix Recovery
2016/05/23 by Srinadh Bhojanapalli, Bhojanapalli, Srinadh, Behnam Neyshabur +3 · 12 citations
Engineering · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Microwave Imaging and Scattering Analysis #Numerical methods in inverse problems #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques
- Path-SGD: Path-Normalized Optimization in Deep Neural Networks
2015/06/08 by Behnam Neyshabur, Ruslan Salakhutdinov, Neyshabur, Behnam +3 · 12 citations
Computer Science · Engineering · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case
2019/10/03 by Greg Ongie, Ongie, Greg, Rebecca Willett +5 · 1 voice · 12 citations
Computer Science · Engineering · Physics and Astronomy · #Model Reduction and Neural Networks #Neural Networks and Applications #Numerical methods in engineering #VLSI and Analog Circuit Testing #VLSI and FPGA Design Techniques #cs.LG #stat.ML
- Learning Non-Discriminatory Predictors
2017/02/20 by Blake Woodworth, Suriya Gunasekar, Woodworth, Blake +5 · 17 citations
Computer Science · #Face and Expression Recognition #Fuzzy Logic and Control Systems
- Geometry of Optimization and Implicit Regularization in Deep Learning
2017/05/08 by Behnam Neyshabur, Ryota Tomioka, Neyshabur, Behnam +5 · 13 citations
Computer Science · Engineering · #Advanced Numerical Analysis Techniques #FOS: Computer and information sciences #Image and Object Detection Techniques #Machine Learning (cs.LG) #Medical Image Segmentation Techniques
- Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
2018/06/29 by Andrew Cotter, Cotter, Andrew, Maya R. Gupta +13 · 10 citations
Computer Science · Social Sciences · #Explainable Artificial Intelligence (XAI) #Ethics and Social Impacts of AI #Adversarial Robustness in Machine Learning
- Minibatch vs Local SGD for Heterogeneous Distributed Learning
2020/06/08 by Blake Woodworth, Kumar Kshitij Patel, Woodworth, Blake +3 · 14 citations
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Privacy-Preserving Technologies in Data #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- On the Universality of Online Mirror Descent
2011/07/20 by Nati Srebro, Nathan Srebro, Srebro, Nathan +4 · 1 voice · 7 citations
Decision Sciences · Computer Science · #cs.LG
- Is Local SGD Better than Minibatch SGD?
2020/02/18 by Blake Woodworth, Woodworth, Blake, Kumar Kshitij Patel +13 · 13 citations
Computer Science · Decision Sciences · Medicine · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #MRI in cancer diagnosis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Privacy-Preserving Technologies in Data
- Convergence of Gradient Descent on Separable Data
2018/03/05 by Mor Shpigel Nacson, Nacson, Mor Shpigel, Jason D. Lee +9 · 11 citations
Computer Science · Engineering · Mathematics · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Markov Chains and Monte Carlo Methods
- The Complexity of Making the Gradient Small in Stochastic Convex\n Optimization
2019/02/12 by Dylan J. Foster, Ayush Sekhari, Foster, Dylan J. +9 · 7 citations
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #Complexity and Algorithms in Graphs #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Stochastic Gradient Descent on Separable Data: Exact Convergence with a\n Fixed Learning Rate
2018/06/05 by Mor Shpigel Nacson, Nacson, Mor Shpigel, Nathan Srebro +3 · 9 citations
Computer Science · Engineering · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Efficient Distributed Learning with Sparsity
2016/05/25 by Jialei Wang, Wang, Jialei, Mladen Kolar +5 · 6 citations
Engineering · Mathematics · Computer Science · #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Distributed Sensor Networks and Detection Algorithms
- Does Invariant Risk Minimization Capture Invariance?
2021/01/04 by Pritish Kamath, Akilesh Tangella, Kamath, Pritish +5 · 8 citations
Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Bayesian Inference
- Mini-Batch Primal and Dual Methods for SVMs
2013/03/10 by Martin Takáč, Avleen S. Bijral, Takáč, Martin +5 · 8 citations
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Neural Networks and Applications #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Implicit Bias in Deep Linear Classification: Initialization Scale vs\n Training Accuracy
2020/07/13 by Edward Moroshko, Moroshko, Edward, Suriya Gunasekar +9 · 5 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
- Dropout: Explicit Forms and Capacity Control
2020/03/06 by Raman Arora, Peter L. Bartlett, Arora, Raman +5 · 8 citations
Computer Science · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Stochastic Gradient Optimization Techniques
- On Symmetric and Asymmetric LSHs for Inner Product Search
2014/10/21 by Behnam Neyshabur, Neyshabur, Behnam, Nathan Srebro +1 · 4 citations
Computer Science · #Advanced Image and Video Retrieval Techniques #Algorithms and Data Compression #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Metaheuristic Optimization Algorithms Research
- How do infinite width bounded norm networks look in function space?
2019/02/13 by Pedro Savarese, Savarese, Pedro, Itay Evron +5 · 4 citations
Computer Science · Engineering · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- On the Power of Differentiable Learning versus PAC and SQ Learning
2021/08/09 by Emmanuel Abbé, Pritish Kamath, Abbe, Emmanuel +7 · 5 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods #Stochastic Gradient Optimization Techniques
- Continual Learning in Linear Classification on Separable Data
2023/06/06 by Itay Evron, Edward Moroshko, Evron, Itay +11 · 6 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA)
- Understanding the Eluder Dimension
2021/04/14 by Gene Li, Li, Gene, Pritish Kamath +5 · 4 citations
Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Optimization and Search Problems #Computability, Logic, AI Algorithms
- Lower Bound for Randomized First Order Convex Optimization
2017/09/11 by Blake Woodworth, Nathan Srebro, Woodworth, Blake +1 · 1 voice · 4 citations
Computer Science · Engineering · Mathematics · #Complexity and Algorithms in Graphs #FOS: Mathematics #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #math.OC
- Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm
2010/02/14 by Ruslan Salakhutdinov, Salakhutdinov, Ruslan, Nathan Srebro +1 · 3 citations
Engineering · #Advanced Adaptive Filtering Techniques #FOS: Computer and information sciences #Indoor and Outdoor Localization Technologies #Machine Learning (cs.LG) #Sparse and Compressive Sensing Techniques
- Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and\n Benign Overfitting
2021/06/17 by Frederic Koehler, Koehler, Frederic, Lijia Zhou +5 · 4 citations
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST)
- Fast-rate and optimistic-rate error bounds for L1-regularized regression
2011/08/01 by Rina Foygel, Foygel, Rina, Nathan Srebro +1 · 2 citations
Computer Science · Engineering · Mathematics · #Distributed Sensor Networks and Detection Algorithms #FOS: Mathematics #Numerical methods in inverse problems #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST)
- Distributed Multitask Learning
2015/10/02 by Jialei Wang, Mladen Kolar, Wang, Jialei +3 · 2 citations
Computer Science · Engineering · #Distributed Sensor Networks and Detection Algorithms #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques
- On Uniform Convergence and Low-Norm Interpolation Learning
2020/06/10 by Lijia Zhou, Zhou, Lijia, Danica J. Sutherland +3 · 2 citations
Computer Science · Engineering · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques
- The Min-Max Complexity of Distributed Stochastic Convex Optimization\n with Intermittent Communication
2021/02/02 by Blake Woodworth, Woodworth, Blake, Brian Bullins +5 · 3 citations
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Cooperative Communication and Network Coding #Energy Efficient Wireless Sensor Networks #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Privacy-Preserving Technologies in Data #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels
2021/03/01 by Eran Malach, Pritish Kamath, Malach, Eran +5 · 3 citations
Computer Science · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
- Path-Normalized Optimization of Recurrent Neural Networks with ReLU\n Activations
2016/05/23 by Behnam Neyshabur, Neyshabur, Behnam, Yuhuai Wu +5 · 2 citations
Computer Science · Physics and Astronomy · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Natural Language Processing Techniques #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE) #Topic Modeling
- Matrix reconstruction with the local max norm
2012/10/18 by Rina Foygel, Nathan Srebro, Foygel, Rina +3 · 1 citation
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- PENCIL: Long Thoughts with Short Memory
2025/03/18 by Chenxiao Yang, Nathan Srebro, Yang, Chenxiao +5 · 1 voice · 5 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.CL #cs.LG
- Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory
2019/07/01 by Blake Woodworth, Nathan Srebro, Woodworth, Blake +1 · 1 citation
Computer Science · #Complexity and Algorithms in Graphs #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Optimization and Control (math.OC) #Optimization and Search Problems
- From Fair Decision Making to Social Equality
2018/12/07 by Hussein Mozannar, Mesrob I. Ohannessian, Mozannar, Hussein +3 · 1 citation
Decision Sciences · Social Sciences · #Computers and Society (cs.CY) #Experimental Behavioral Economics Studies #FOS: Computer and information sciences #Game Theory and Applications #Income, Poverty, and Inequality #K.4 #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- A Theory of Learning with Autoregressive Chain of Thought
2025/03/11 by Nirmit Joshi, Gal Vardi, Joshi, Nirmit +11 · 4 citations
Psychology · Social Sciences · #Artificial Intelligence (cs.AI) #Computational Complexity (cs.CC) #Education and Critical Thinking Development #FOS: Computer and information sciences #Innovative Teaching and Learning Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Exponential Family Model-Based Reinforcement Learning via Score Matching
2021/12/28 by Gene Li, Junbo Li, Li, Gene +8 · 1 citation
Decision Sciences · Computer Science · Economics, Econometrics and Finance · #Advanced Bandit Algorithms Research #Reinforcement Learning in Robotics #Sports Analytics and Performance
- Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization
2022/02/27 by Idan Amir, Amir, Idan, Roi Livni +3 · 1 citation
Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Stochastic Gradient Optimization Techniques
- Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization
2023/03/02 by Spencer Frei, Gal Vardi, Frei, Spencer +5 · 1 citation
Computer Science · #Bayesian Modeling and Causal Inference #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Data-Dependent Path Normalization in Neural Networks
2015/11/20 by Behnam Neyshabur, Ryota Tomioka, Neyshabur, Behnam +5 · 1 citation
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications
- Noisy Interpolation Learning with Shallow Univariate ReLU Networks
2023/07/28 by Nirmit Joshi, Joshi, Nirmit, Gal Vardi +3 · 1 citation
Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning and Data Classification #Neural Networks and Applications
- Concentration-Based Guarantees for Low-Rank Matrix Reconstruction
2011/02/18 by Rina Foygel, Nathan Srebro, Foygel, Rina +1 · 1 citation
Computer Science · Engineering · Medicine · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Medical Image Segmentation Techniques #Medical Imaging Techniques and Applications #Sparse and Compressive Sensing Techniques
- Learning single-index models via harmonic decomposition
2025/06/11 by Nirmit Joshi, Hugo Koubbi, Joshi, Nirmit +5 · 3 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST) #Tensor decomposition and applications
- A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
2022/10/21 by Lijia Zhou, Zhou, Lijia, Frederic Koehler +7 · 1 citation
Mathematics · Computer Science · #Statistical Methods and Inference #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods
- The Price of Implicit Bias in Adversarially Robust Generalization
2024/06/07 by Nikolaos Tsilivis, Natalie C. Frank, Tsilivis, Nikolaos +5 · 1 citation
Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Weak-to-Strong Generalization Even in Random Feature Networks, Provably
2025/03/04 by Medvedev, Marko, Kaifeng Lyu, Dingli Yu +8 · 1 citation
Computer Science · #Face and Expression Recognition #Neural Networks and Applications #Anomaly Detection Techniques and Applications
- Hierarchical Domain Generalization
2026/07/17 by Chenxiao Yang, Zhiyuan Li, Shai Ben-David +1
#cs.LG
- On Incentivized Exploration beyond Bayesianism and Full-Information
2026/07/14 by Dimitar Chakarov, Lee Cohen, Nathan Srebro
#cs.GT #cs.LG