Surbhi Goel - RankMe

88 papers A* 34A 3Journal 50Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Collaborative Prediction: Tractable Information Aggregation via Agreement. SODA Natalie Collina, Ira Globus-Harris, Surbhi Goel, Varun Gupta, Aaron Roth, Mirah Shi
2026	J	`jnl`	Model Agreement via Anchoring. CoRR Eric Eaton, Surbhi Goel, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell
2026	J	`jnl`	Personalization Aids Pluralistic Alignment Under Competition. CoRR Natalie Collina, Surbhi Goel, Aaron Roth, Mirah Shi
2026	J	`jnl`	Reliable Abstention under Adversarial Injections: Tight Lower Bounds and New Upper Bounds. CoRR Ezra Edelman, Surbhi Goel
2025	A*	`conf`	A Theory of Learning with Autoregressive Chain of Thought. COLT Nirmit Joshi, Gal Vardi, Adam Block, Surbhi Goel, Zhiyuan Li, Theodor Misiakiewicz, Nathan Srebro
2025	J	`jnl`	A Theory of Learning with Autoregressive Chain of Thought. CoRR Nirmit Joshi, Gal Vardi, Adam Block, Surbhi Goel, Zhiyuan Li, Theodor Misiakiewicz, Nathan Srebro
2025	J	`jnl`	Collaborative Prediction: Tractable Information Aggregation via Agreement. CoRR Natalie Collina, Ira Globus-Harris, Surbhi Goel, Varun Gupta, Aaron Roth, Mirah Shi
2025	A*	`conf`	Conformal Language Model Reasoning with Coherent Factuality. ICLR Maxon Rubin-Toles, Maya Gambhir, Keshav Ramji, Aaron Roth, Surbhi Goel
2025	J	`jnl`	Conformal Language Model Reasoning with Coherent Factuality. CoRR Maxon Rubin-Toles, Maya Gambhir, Keshav Ramji, Aaron Roth, Surbhi Goel
2025	J	`jnl`	Emergent Alignment via Competition. CoRR Natalie Collina, Surbhi Goel, Aaron Roth, Emily Ryu, Mirah Shi
2025	J	`jnl`	In Good GRACEs: Principled Teacher Selection for Knowledge Distillation. CoRR Abhishek Panigrahi, Bingbin Liu, Sadhika Malladi, Sham M. Kakade, Surbhi Goel
2025	A*	`conf`	Logicbreaks: A Framework for Understanding Subversion of Rule-based Inference. ICLR Anton Xue, Avishree Khare, Rajeev Alur, Surbhi Goel, Eric Wong
2025	J	`jnl`	Probabilistic Stability Guarantees for Feature Attributions. CoRR Helen Jin, Anton Xue, Weiqiu You, Surbhi Goel, Eric Wong
2025	A*	`conf`	Progressive distillation induces an implicit curriculum. ICLR Abhishek Panigrahi, Bingbin Liu, Sadhika Malladi, Andrej Risteski, Surbhi Goel
2025	J	`jnl`	Testing Noise Assumptions of Learning Algorithms. CoRR Surbhi Goel, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2025	A*	`conf`	Tractable Agreement Protocols. STOC Natalie Collina, Surbhi Goel, Varun Gupta, Aaron Roth
2025	J	`jnl`	Why Do Transformers Fail to Forecast Time Series In-Context? CoRR Yufa Zhou, Yixiao Wang, Surbhi Goel, Anru R. Zhang
2024	J	`jnl`	Complexity Matters: Dynamics of Feature Learning in the Presence of Spurious Correlations. CoRR Guanwen Qiu, Da Kuang, Surbhi Goel
2024	A*	`conf`	Complexity Matters: Feature Learning in the Presence of Spurious Correlations. ICML Guanwen Qiu, Da Kuang, Surbhi Goel
2024	J	`jnl`	Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic Tasks. CoRR Mahdi Sabbaghi, George J. Pappas, Hamed Hassani, Surbhi Goel
2024	J	`jnl`	Logicbreaks: A Framework for Understanding Subversion of Rule-based Inference. CoRR Anton Xue, Avishree Khare, Rajeev Alur, Surbhi Goel, Eric Wong
2024	J	`jnl`	Progressive distillation induces an implicit curriculum. CoRR Abhishek Panigrahi, Bingbin Liu, Sadhika Malladi, Andrej Risteski, Surbhi Goel
2024	A*	`conf`	Stochastic Bandits with ReLU Neural Networks. ICML Kan Xu, Hamsa Bastani, Surbhi Goel, Osbert Bastani
2024	J	`jnl`	Stochastic Bandits with ReLU Neural Networks. CoRR Kan Xu, Hamsa Bastani, Surbhi Goel, Osbert Bastani
2024	A*	`conf`	The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains. NeurIPS Ezra Edelman, Nikolaos Tsilivis, Benjamin L. Edelman, Eran Malach, Surbhi Goel
2024	J	`jnl`	The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains. CoRR Benjamin L. Edelman, Ezra Edelman, Surbhi Goel, Eran Malach, Nikolaos Tsilivis
2024	A*	`conf`	Tolerant Algorithms for Learning with Arbitrary Covariate Shift. NeurIPS Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan
2024	J	`jnl`	Tolerant Algorithms for Learning with Arbitrary Covariate Shift. CoRR Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan
2024	J	`jnl`	Tractable Agreement Protocols. CoRR Natalie Collina, Surbhi Goel, Varun Gupta, Aaron Roth
2023	A*	`conf`	Adversarial Resilience in Sequential Prediction via Abstention. NeurIPS Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty
2023	J	`jnl`	Adversarial Resilience in Sequential Prediction via Abstention. CoRR Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty
2023	A*	`conf`	Exposing Attention Glitches with Flip-Flop Language Modeling. NeurIPS Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
2023	J	`jnl`	Exposing Attention Glitches with Flip-Flop Language Modeling. CoRR Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
2023	A*	`conf`	Learning Narrow One-Hidden-Layer ReLU Networks. COLT Sitan Chen, Zehao Dou, Surbhi Goel, Adam R. Klivans, Raghu Meka
2023	J	`jnl`	Learning Narrow One-Hidden-Layer ReLU Networks. CoRR Sitan Chen, Zehao Dou, Surbhi Goel, Adam R. Klivans, Raghu Meka
2023	A*	`conf`	Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck. NeurIPS Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
2023	J	`jnl`	Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck. CoRR Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
2023	A*	`conf`	Transformers Learn Shortcuts to Automata. ICLR Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
2022	A*	`conf`	Anti-Concentrated Confidence Bonuses For Scalable Exploration. ICLR Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
2022	A*	`conf`	Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit. NeurIPS Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
2022	J	`jnl`	Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit. CoRR Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
2022	A*	`conf`	Inductive Biases and Variable Creation in Self-Attention Mechanisms. ICML Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Cyril Zhang
2022	A	`conf`	Investigating the Role of Negatives in Contrastive Representation Learning. AISTATS Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
2022	A*	`conf`	Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms. NeurIPS Surbhi Goel, Sham M. Kakade, Adam Kalai, Cyril Zhang
2022	J	`jnl`	Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms. CoRR Surbhi Goel, Sham M. Kakade, Adam Tauman Kalai, Cyril Zhang
2022	J	`jnl`	Transformers Learn Shortcuts to Automata. CoRR Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
2022	A*	`conf`	Understanding Contrastive Learning Requires Incorporating Inductive Biases. ICML Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy
2022	J	`jnl`	Understanding Contrastive Learning Requires Incorporating Inductive Biases. CoRR Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy
2021	A*	`conf`	Acceleration via Fractal Learning Rate Schedules. ICML Naman Agarwal, Surbhi Goel, Cyril Zhang
2021	J	`jnl`	Acceleration via Fractal Learning Rate Schedules. CoRR Naman Agarwal, Surbhi Goel, Cyril Zhang
2021	J	`jnl`	Anti-Concentrated Confidence Bonuses for Scalable Exploration. CoRR Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
2021	A*	`conf`	Gone Fishing: Neural Active Learning with Fisher Embeddings. NeurIPS Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
2021	J	`jnl`	Gone Fishing: Neural Active Learning with Fisher Embeddings. CoRR Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
2021	J	`jnl`	Inductive Biases and Variable Creation in Self-Attention Mechanisms. CoRR Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Cyril Zhang
2021	J	`jnl`	Investigating the Role of Negatives in Contrastive Representation Learning. CoRR Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
2021	A*	`conf`	Statistical Estimation from Dependent Data. ICML Anthimos Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis
2021	J	`jnl`	Statistical Estimation from Dependent Data. CoRR Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Surbhi Goel, Anthimos Vardis Kandiros
2021	A	`conf`	Tight Hardness Results for Training Depth-2 ReLU Networks. ITCS Surbhi Goel, Adam R. Klivans, Pasin Manurangsi, Daniel Reichman
2020	A*	`conf`	Approximation Schemes for ReLU Regression. COLT Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans, Mahdi Soltanolkotabi
2020	J	`jnl`	Approximation Schemes for ReLU Regression. CoRR Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans, Mahdi Soltanolkotabi
2020	A*	`conf`	Efficiently Learning Adversarially Robust Halfspaces with Noise. ICML Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro
2020	J	`jnl`	Efficiently Learning Adversarially Robust Halfspaces with Noise. CoRR Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro
2020	A*	`conf`	From Boltzmann Machines to Neural Networks and Back Again. NeurIPS Surbhi Goel, Adam R. Klivans, Frederic Koehler
2020	J	`jnl`	From Boltzmann Machines to Neural Networks and Back Again. CoRR Surbhi Goel, Adam R. Klivans, Frederic Koehler
2020	A	`conf`	Learning Ising and Potts Models with Latent Variables. AISTATS Surbhi Goel
2020	A*	`conf`	Learning Mixtures of Graphs from Epidemic Cascades. ICML Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis
2020	A*	`conf`	Statistical-Query Lower Bounds via Functional Gradients. NeurIPS Surbhi Goel, Aravind Gollakota, Adam R. Klivans
2020	J	`jnl`	Statistical-Query Lower Bounds via Functional Gradients. CoRR Surbhi Goel, Aravind Gollakota, Adam R. Klivans
2020	A*	`conf`	Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent. ICML Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam R. Klivans
2020	J	`jnl`	Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent. CoRR Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam R. Klivans
2020	J	`jnl`	Tight Hardness Results for Training Depth-2 ReLU Networks. CoRR Surbhi Goel, Adam R. Klivans, Pasin Manurangsi, Daniel Reichman
2019	J	`jnl`	Disentangling Mixtures of Epidemics on Graphs. CoRR Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis
2019	A*	`conf`	Learning Ising Models with Independent Failures. COLT Surbhi Goel, Daniel M. Kane, Adam R. Klivans
2019	J	`jnl`	Learning Ising Models with Independent Failures. CoRR Surbhi Goel, Daniel M. Kane, Adam R. Klivans
2019	A*	`conf`	Learning Neural Networks with Two Nonlinear Layers in Polynomial Time. COLT Surbhi Goel, Adam R. Klivans
2019	J	`jnl`	Learning Restricted Boltzmann Machines with Arbitrary External Fields. CoRR Surbhi Goel
2019	J	`jnl`	Learning Two layer Networks with Multinomial Activation and High Thresholds. CoRR Surbhi Goel, Rina Panigrahy
2019	J	`jnl`	Quantifying Perceptual Distortion of Adversarial Examples. CoRR Matt Jordan, Naren Manoj, Surbhi Goel, Alexandros G. Dimakis
2019	A*	`conf`	Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals. NeurIPS Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans
2019	J	`jnl`	Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals. CoRR Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans
2018	J	`jnl`	Improved Learning of One-hidden-layer Convolutional Neural Networks with Overlaps. CoRR Simon S. Du, Surbhi Goel
2018	A*	`conf`	Learning One Convolutional Layer with Overlapping Patches. ICML Surbhi Goel, Adam R. Klivans, Raghu Meka
2018	J	`jnl`	Learning One Convolutional Layer with Overlapping Patches. CoRR Surbhi Goel, Adam R. Klivans, Raghu Meka
2017	—	`conf`	Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks. NIPS Surbhi Goel, Adam R. Klivans
2017	J	`jnl`	Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks. CoRR Surbhi Goel, Adam R. Klivans
2017	J	`jnl`	Learning Depth-Three Neural Networks in Polynomial Time. CoRR Surbhi Goel, Adam R. Klivans
2017	A*	`conf`	Reliably Learning the ReLU in Polynomial Time. COLT Surbhi Goel, Varun Kanade, Adam R. Klivans, Justin Thaler
2016	J	`jnl`	Reliably Learning the ReLU in Polynomial Time. CoRR Surbhi Goel, Varun Kanade, Adam R. Klivans, Justin Thaler