Surbhi Goel
37 papers · 2017–2026 · 5 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 9 separate collaboration groups - the largest holds only 43% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Surbhi Goel?
3 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Adam Klivans, Sushrut Karmalkar, Adam R. Klivans
16 papers
· 2017–2026
· COLT, NeurIPS, ICML
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Testing Noise Assumptions of Learning Algorithms
COLT 2026
A Theory of Learning with Autoregressive Chain of Thought
COLT 2025
Tolerant Algorithms for Learning with Arbitrary Covariate Shift
NeurIPS 2024
Adversarial Resilience in Sequential Prediction via Abstention
NeurIPS 2023
Learning Narrow One-Hidden-Layer ReLU Networks
COLT 2023
Approximation Schemes for ReLU Regression
COLT 2020
Efficiently Learning Adversarially Robust Halfspaces with Noise
ICML 2020
From Boltzmann Machines to Neural Networks and Back Again
NeurIPS 2020
Statistical-Query Lower Bounds via Functional Gradients
NeurIPS 2020
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent
ICML 2020
Learning Ising Models with Independent Failures
COLT 2019
Learning Neural Networks with Two Nonlinear Layers in Polynomial Time
COLT 2019
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals
NeurIPS 2019
Learning One Convolutional Layer with Overlapping Patches
ICML 2018
Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks
NeurIPS 2017
Reliably Learning the ReLU in Polynomial Time
COLT 2017
6 papers whose co-authors appear nowhere else under this name
Logicbreaks: A Framework for Understanding Subversion of Rule-based Inference
ICLR 2025
Complexity Matters: Feature Learning in the Presence of Spurious Correlations
ICML 2024
Stochastic Bandits with ReLU Neural Networks
ICML 2024
Statistical Estimation from Dependent Data
ICML 2021
Learning Ising and Potts Models with Latent Variables
AISTATS 2020
Learning Mixtures of Graphs from Epidemic Cascades
ICML 2020