• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 299 matches

• 2024
• 
  Maryam Aliakbarpour, Konstantina Bairaktari, Gavin Brown, Adam Smith, Nathan Srebro, Jonathan R. Ullman:
  Metalearning with Very Few Samples Per Task. COLT 2024: 46-93
• 
  Suzanna Parkinson, Greg Ongie, Rebecca Willett, Ohad Shamir, Nathan Srebro:
  Depth Separation in Norm-Bounded Infinite-Width Neural Networks. COLT 2024: 4082-4114
• 
  Kumar Kshitij Patel, Margalit Glasgow, Ali Zindari, Lingxiao Wang, Sebastian U. Stich, Ziheng Cheng, Nirmit Joshi, Nathan Srebro:
  The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication. COLT 2024: 4115-4157
• 
  Anmol Kabra, Mina Karzand, Tosca Lechner, Nati Srebro, Serena Lutong Wang:
  Score Design for Multi-Criteria Incentivization. FORC 2024: 8:1-8:22
• 
  Nirmit Joshi, Gal Vardi, Nathan Srebro:
  Noisy Interpolation Learning with Shallow Univariate ReLU Networks. ICLR 2024
• 
  Lijia Zhou, James B. Simon, Gal Vardi, Nathan Srebro:
  An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression. ICLR 2024
• 
  Gon Buzaglo, Itamar Harel, Mor Shpigel Nacson, Alon Brutzkus, Nathan Srebro, Daniel Soudry:
  How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers. ICML 2024
• 
  Gon Buzaglo, Itamar Harel, Mor Shpigel Nacson, Alon Brutzkus, Nathan Srebro, Daniel Soudry:
  How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers. CoRR abs/2402.06323 (2024)
• 
  Suzanna Parkinson, Greg Ongie, Rebecca Willett, Ohad Shamir, Nathan Srebro:
  Depth Separation in Norm-Bounded Infinite-Width Neural Networks. CoRR abs/2402.08808 (2024)
• 
  Kumar Kshitij Patel, Margalit Glasgow, Ali Zindari, Lingxiao Wang, Sebastian U. Stich, Ziheng Cheng, Nirmit Joshi, Nathan Srebro:
  The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication. CoRR abs/2405.11667 (2024)
• 
  Nikolaos Tsilivis, Natalie Frank, Nathan Srebro, Julia Kempe:
  The Price of Implicit Bias in Adversarially Robust Generalization. CoRR abs/2406.04981 (2024)
• 
  Nirmit Joshi, Theodor Misiakiewicz, Nathan Srebro:
  On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries. CoRR abs/2407.05622 (2024)
• 2023
• 
  Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Nathan Srebro, Blake E. Woodworth:
  Lower bounds for non-convex stochastic optimization. Math. Program. 199(1): 165-214 (2023)
• 
  Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro:
  Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization. COLT 2023: 3173-3228
• 
  Naren Sarayu Manoj, Nathan Srebro:
  Shortest Program Interpolation Learning. COLT 2023: 4881-4901
• 
  Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro, Wei Hu:
  Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data. ICLR 2023
• 
  Itay Evron, Edward Moroshko, Gon Buzaglo, Maroun Khriesh, Badea Marjieh, Nathan Srebro, Daniel Soudry:
  Continual Learning in Linear Classification on Separable Data. ICML 2023: 9440-9484
• 
  Kumar Kshitij Patel, Lingxiao Wang, Aadirupa Saha, Nathan Srebro:
  Federated Online and Bandit Convex Optimization. ICML 2023: 27439-27460
• 
  Amit Daniely, Nati Srebro, Gal Vardi:
  Most Neural Networks Are Almost Learnable. NeurIPS 2023
• 
  Amit Daniely, Nati Srebro, Gal Vardi:
  Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy. NeurIPS 2023
• 
  Spencer Frei, Gal Vardi, Peter L. Bartlett, Nati Srebro:
  The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks. NeurIPS 2023
• 
  Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari, Nati Srebro:
  When is Agnostic Reinforcement Learning Statistically Tractable? NeurIPS 2023
• 
  Lijia Zhou, Zhen Dai, Frederic Koehler, Nati Srebro:
  Uniform Convergence with Square-Root Lipschitz Loss. NeurIPS 2023
• 
  Naren Sarayu Manoj, Nathan Srebro:
  Interpolation Learning With Minimum Description Length. CoRR abs/2302.07263 (2023)
• 
  Amit Daniely, Nathan Srebro, Gal Vardi:
  Efficiently Learning Neural Networks: What Assumptions May Suffice? CoRR abs/2302.07426 (2023)
• 
  Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro:
  The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks. CoRR abs/2303.01456 (2023)
• 
  Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro:
  Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization. CoRR abs/2303.01462 (2023)
• 
  Amit Daniely, Nathan Srebro, Gal Vardi:
  Most Neural Networks Are Almost Learnable. CoRR abs/2305.16508 (2023)
• 
  Itay Evron, Edward Moroshko, Gon Buzaglo, Maroun Khriesh, Badea Marjieh, Nathan Srebro, Daniel Soudry:
  Continual Learning in Linear Classification on Separable Data. CoRR abs/2306.03534 (2023)
• 
  Lijia Zhou, James B. Simon, Gal Vardi, Nathan Srebro:
  An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression. CoRR abs/2306.13185 (2023)

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