Publications & Preprints

(2021). Inductive Biases and Variable Creation in Self-Attention Mechanisms.

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(2021). Investigating the Role of Negatives in Contrastive Representation Learning.

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(2021). Gone Fishing: Neural Active Learning with Fisher Embeddings. NeurIPS.

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(2021). Statistical Estimation from Dependent Data. ICML.

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(2021). Acceleration via Fractal Learning Rate Schedules. ICML.

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(2021). Tight Hardness Results for Training Depth-2 ReLU Networks. ITCS.

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(2020). Statistical-Query Lower Bounds via Functional Gradients. NeurIPS.

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(2020). From Boltzmann Machines to Neural Networks and Back Again. NeurIPS.

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(2020). Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent. ICML.

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(2020). Learning Mixtures of Graphs from Epidemic Cascades. ICML.

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(2020). Efficiently Learning Adversarially Robust Halfspaces with Noise. ICML.

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(2020). Approximation Schemes for ReLU Regression. COLT.

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(2019). Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals. NeurIPS (Spotlight).

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(2019). Learning Ising Models with Independent Failures. COLT.

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(2019). Quantifying Perceptual Distortion of Adversarial Examples.

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(2018). Learning One Convolutional Layer with Overlapping Patches. ICML.

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(2017). Reliably Learning the ReLU in Polynomial Time. COLT.

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