Adam Klivans

Equivalence of Coarse and Fine-Grained Models for Learning with Distribution Shift COLT 2026 Sandwiching Polynomials for Geometric Concepts with Low Intrinsic Dimension COLT 2026 Testing Noise Assumptions of Learning Algorithms COLT 2026 Distilling Structural Representations into Protein Sequence Models ICLR 2025 Does Generation Require Memorization? Creative Diffusion Models using Ambient Diffusion ICML 2025 Learning Constant-Depth Circuits in Malicious Noise Models COLT 2025 Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees ICLR 2025 An Efficient Tester-Learner for Halfspaces ICLR 2024 Evolution-Inspired Loss Functions for Protein Representation Learning ICML 2024 Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds COLT 2024 Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension COLT 2024 Testable Learning with Distribution Shift COLT 2024 Agnostically Learning Single-Index Models using Omnipredictors NeurIPS 2023 Ambient Diffusion: Learning Clean Distributions from Corrupted Data NeurIPS 2023 HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing ICLR 2023 Learning Mixtures of Gaussians Using the DDPM Objective NeurIPS 2023 Learning Narrow One-Hidden-Layer ReLU Networks COLT 2023 Predicting a Protein's Stability under a Million Mutations NeurIPS 2023 Tester-Learners for Halfspaces: Universal Algorithms NeurIPS 2023 Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks NeurIPS 2022 Efficiently Learning One Hidden Layer ReLU Networks From Queries NeurIPS 2021 From Boltzmann Machines to Neural Networks and Back Again NeurIPS 2020 Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection ICML 2020 Statistical-Query Lower Bounds via Functional Gradients NeurIPS 2020 Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent ICML 2020 List-decodable Linear Regression NeurIPS 2019 Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals NeurIPS 2019 Efficient Algorithms for Outlier-Robust Regression COLT 2018 Hyperparameter optimization: a spectral approach ICLR 2018 Learning One Convolutional Layer with Overlapping Patches ICML 2018 Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks NeurIPS 2017 Exact MAP Inference by Avoiding Fractional Vertices ICML 2017 Reliably Learning the ReLU in Polynomial Time COLT 2017 Sparse Polynomial Learning and Graph Sketching NeurIPS 2014 Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching COLT 2013