Surbhi Goel

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 65

Top Topics

Top Venues

Publications

Kan Xu, Hamsa Bastani, Surbhi Goel, Osbert Bastani
Stochastic Bandits with ReLU Neural Networks. CoRR (2024)
Mahdi Sabbaghi, George J. Pappas, Hamed Hassani, Surbhi Goel
Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic Tasks. CoRR (2024)
Benjamin L. Edelman, Ezra Edelman, Surbhi Goel, Eran Malach, Nikolaos Tsilivis
The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains. CoRR (2024)
Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan
Tolerant Algorithms for Learning with Arbitrary Covariate Shift. CoRR (2024)
Anton Xue, Avishree Khare, Rajeev Alur, Surbhi Goel, Eric Wong
Logicbreaks: A Framework for Understanding Subversion of Rule-based Inference. CoRR (2024)
Guanwen Qiu, Da Kuang, Surbhi Goel
Complexity Matters: Dynamics of Feature Learning in the Presence of Spurious Correlations. CoRR (2024)
Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck. NeurIPS (2023)
Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty
Adversarial Resilience in Sequential Prediction via Abstention. CoRR (2023)
Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty
Adversarial Resilience in Sequential Prediction via Abstention. NeurIPS (2023)
Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
Exposing Attention Glitches with Flip-Flop Language Modeling. NeurIPS (2023)
Sitan Chen, Zehao Dou, Surbhi Goel, Adam R. Klivans, Raghu Meka
Learning Narrow One-Hidden-Layer ReLU Networks. CoRR (2023)
Sitan Chen, Zehao Dou, Surbhi Goel, Adam R. Klivans, Raghu Meka
Learning Narrow One-Hidden-Layer ReLU Networks. COLT (2023)
Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
Exposing Attention Glitches with Flip-Flop Language Modeling. CoRR (2023)
Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck. CoRR (2023)
Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
Transformers Learn Shortcuts to Automata. ICLR (2023)
Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy
Understanding Contrastive Learning Requires Incorporating Inductive Biases. CoRR (2022)
Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Cyril Zhang
Inductive Biases and Variable Creation in Self-Attention Mechanisms. ICML (2022)
Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy
Understanding Contrastive Learning Requires Incorporating Inductive Biases. ICML (2022)
Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit. CoRR (2022)
Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit. NeurIPS (2022)
Surbhi Goel, Sham M. Kakade, Adam Kalai, Cyril Zhang
Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms. NeurIPS (2022)
Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
Transformers Learn Shortcuts to Automata. CoRR (2022)
Surbhi Goel, Sham M. Kakade, Adam Tauman Kalai, Cyril Zhang
Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms. CoRR (2022)
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
Investigating the Role of Negatives in Contrastive Representation Learning. AISTATS (2022)
Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
Anti-Concentrated Confidence Bonuses For Scalable Exploration. ICLR (2022)
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
Gone Fishing: Neural Active Learning with Fisher Embeddings. CoRR (2021)
Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
Anti-Concentrated Confidence Bonuses for Scalable Exploration. CoRR (2021)
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
Investigating the Role of Negatives in Contrastive Representation Learning. CoRR (2021)
Anthimos Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis
Statistical Estimation from Dependent Data. ICML (2021)
Naman Agarwal, Surbhi Goel, Cyril Zhang
Acceleration via Fractal Learning Rate Schedules. CoRR (2021)
Surbhi Goel, Adam R. Klivans, Pasin Manurangsi, Daniel Reichman
Tight Hardness Results for Training Depth-2 ReLU Networks. ITCS (2021)
Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Cyril Zhang
Inductive Biases and Variable Creation in Self-Attention Mechanisms. CoRR (2021)
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
Gone Fishing: Neural Active Learning with Fisher Embeddings. NeurIPS (2021)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Surbhi Goel, Anthimos Vardis Kandiros
Statistical Estimation from Dependent Data. CoRR (2021)
Naman Agarwal, Surbhi Goel, Cyril Zhang
Acceleration via Fractal Learning Rate Schedules. ICML (2021)
Surbhi Goel, Adam R. Klivans, Frederic Koehler
From Boltzmann Machines to Neural Networks and Back Again. NeurIPS (2020)
Surbhi Goel, Adam R. Klivans, Frederic Koehler
From Boltzmann Machines to Neural Networks and Back Again. CoRR (2020)
Surbhi Goel, Aravind Gollakota, Adam R. Klivans
Statistical-Query Lower Bounds via Functional Gradients. CoRR (2020)
Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro
Efficiently Learning Adversarially Robust Halfspaces with Noise. CoRR (2020)
Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans, Mahdi Soltanolkotabi
Approximation Schemes for ReLU Regression. CoRR (2020)
Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro
Efficiently Learning Adversarially Robust Halfspaces with Noise. ICML (2020)
Surbhi Goel, Aravind Gollakota, Adam R. Klivans
Statistical-Query Lower Bounds via Functional Gradients. NeurIPS (2020)
Surbhi Goel, Adam R. Klivans, Pasin Manurangsi, Daniel Reichman
Tight Hardness Results for Training Depth-2 ReLU Networks. CoRR (2020)
Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam R. Klivans
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent. ICML (2020)
Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis
Learning Mixtures of Graphs from Epidemic Cascades. ICML (2020)
Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans, Mahdi Soltanolkotabi
Approximation Schemes for ReLU Regression. COLT (2020)
Surbhi Goel
Learning Ising and Potts Models with Latent Variables. AISTATS (2020)
Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam R. Klivans
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent. CoRR (2020)
Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis
Disentangling Mixtures of Epidemics on Graphs. CoRR (2019)
Surbhi Goel
Learning Restricted Boltzmann Machines with Arbitrary External Fields. CoRR (2019)
Surbhi Goel, Adam R. Klivans
Learning Neural Networks with Two Nonlinear Layers in Polynomial Time. COLT (2019)
Surbhi Goel, Daniel M. Kane, Adam R. Klivans
Learning Ising Models with Independent Failures. COLT (2019)
Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals. CoRR (2019)
Surbhi Goel, Rina Panigrahy
Learning Two layer Networks with Multinomial Activation and High Thresholds. CoRR (2019)
Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals. NeurIPS (2019)
Matt Jordan, Naren Manoj, Surbhi Goel, Alexandros G. Dimakis
Quantifying Perceptual Distortion of Adversarial Examples. CoRR (2019)
Surbhi Goel, Daniel M. Kane, Adam R. Klivans
Learning Ising Models with Independent Failures. CoRR (2019)
Surbhi Goel, Adam R. Klivans, Raghu Meka
Learning One Convolutional Layer with Overlapping Patches. ICML (2018)
Simon S. Du, Surbhi Goel
Improved Learning of One-hidden-layer Convolutional Neural Networks with Overlaps. CoRR (2018)
Surbhi Goel, Adam R. Klivans, Raghu Meka
Learning One Convolutional Layer with Overlapping Patches. CoRR (2018)
Surbhi Goel, Adam R. Klivans
Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks. NIPS (2017)
Surbhi Goel, Varun Kanade, Adam R. Klivans, Justin Thaler
Reliably Learning the ReLU in Polynomial Time. COLT (2017)
Surbhi Goel, Adam R. Klivans
Learning Depth-Three Neural Networks in Polynomial Time. CoRR (2017)
Surbhi Goel, Adam R. Klivans
Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks. CoRR (2017)
Surbhi Goel, Varun Kanade, Adam R. Klivans, Justin Thaler
Reliably Learning the ReLU in Polynomial Time. CoRR (2016)