Surbhi Goel
35 papers · 2017–2025 · 5 conferences · across top CS/AI conferences
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ICML (10)
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isotonic regression
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Papers
Conformal Language Model Reasoning with Coherent Factuality
ICLR 2025
Progressive distillation induces an implicit curriculum
ICLR 2025
Logicbreaks: A Framework for Understanding Subversion of Rule-based Inference
ICLR 2025
A Theory of Learning with Autoregressive Chain of Thought
COLT 2025
Tolerant Algorithms for Learning with Arbitrary Covariate Shift
NIPS 2024
The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains
NIPS 2024
Stochastic Bandits with ReLU Neural Networks
ICML 2024
Complexity Matters: Feature Learning in the Presence of Spurious Correlations
ICML 2024
Exposing Attention Glitches with Flip-Flop Language Modeling
NIPS 2023
Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck
NIPS 2023
Transformers Learn Shortcuts to Automata
ICLR 2023
Learning Narrow One-Hidden-Layer ReLU Networks
COLT 2023
Adversarial Resilience in Sequential Prediction via Abstention
NIPS 2023
Investigating the Role of Negatives in Contrastive Representation Learning
AISTATS 2022
Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms
NIPS 2022
Understanding Contrastive Learning Requires Incorporating Inductive Biases
ICML 2022
Inductive Biases and Variable Creation in Self-Attention Mechanisms
ICML 2022
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit
NIPS 2022
Anti-Concentrated Confidence Bonuses For Scalable Exploration
ICLR 2022
Acceleration via Fractal Learning Rate Schedules
ICML 2021
Statistical Estimation from Dependent Data
ICML 2021
Gone Fishing: Neural Active Learning with Fisher Embeddings
NIPS 2021
Approximation Schemes for ReLU Regression
COLT 2020
Statistical-Query Lower Bounds via Functional Gradients
NIPS 2020
From Boltzmann Machines to Neural Networks and Back Again
NIPS 2020
Learning Ising and Potts Models with Latent Variables
AISTATS 2020
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent
ICML 2020
Learning Mixtures of Graphs from Epidemic Cascades
ICML 2020
Efficiently Learning Adversarially Robust Halfspaces with Noise
ICML 2020
Learning Neural Networks with Two Nonlinear Layers in Polynomial Time
COLT 2019
Learning Ising Models with Independent Failures
COLT 2019
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals
NIPS 2019
Learning One Convolutional Layer with Overlapping Patches
ICML 2018
Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks
NIPS 2017
Reliably Learning the ReLU in Polynomial Time
COLT 2017