Gollakota, Aravind

8 publications

ICLR 2025 Provable Uncertainty Decomposition via Higher-Order Calibration Gustaf Ahdritz, Aravind Gollakota, Parikshit Gopalan, Charlotte Peale, Udi Wieder

ICLR 2024 An Efficient Tester-Learner for Halfspaces Aravind Gollakota, Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

NeurIPS 2023 Agnostically Learning Single-Index Models Using Omnipredictors Aravind Gollakota, Parikshit Gopalan, Adam Klivans, Konstantinos Stavropoulos

NeurIPS 2023 Ambient Diffusion: Learning Clean Distributions from Corrupted Data Giannis Daras, Kulin Shah, Yuval Dagan, Aravind Gollakota, Alex Dimakis, Adam Klivans

NeurIPS 2023 Tester-Learners for Halfspaces: Universal Algorithms Aravind Gollakota, Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

NeurIPS 2022 Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks Sitan Chen, Aravind Gollakota, Adam Klivans, Raghu Meka

NeurIPS 2020 Statistical-Query Lower Bounds via Functional Gradients Surbhi Goel, Aravind Gollakota, Adam Klivans

ICML 2020 Superpolynomial Lower Bounds for Learning One-Layer Neural Networks Using Gradient Descent Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam Klivans