Aravind Gollakota

8 papers · 2020–2025 · 3 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🗺️ Taxonomy Completionist (11)

Venues

NeurIPS (5) ICLR (2) ICML (1)

Top co-authors

Adam Klivans (7) Konstantinos Stavropoulos (3) Parikshit Gopalan (2) Surbhi Goel (2) Arsen Vasilyan (2) Raghu Meka (1) Giannis Daras (1) Gustaf Ahdritz (1) Sitan Chen (1) Alex Dimakis (1)

Research topics

Machine Learning (7) Optimization & Theory · Machine Learning (7) Core Methods (3) Deep Learning (2) Architectures (1) Learning Types (1) Models (1) Optimization & Theory · Deep Learning (1)

Keywords

agnostic learning (3) learning theory (3) lower bound (2) label noise (2) relu activation (2) neural network (2) testable learning (2) bregman divergence (1) gaussian input (1) gradient descent (1) bayesian inference (1) halfspace learning (1) distribution testing (1) halfspace classification (1) moment matching (1) generative model (1) diffusion model (1) learning hardness (1) compressed sensing (1) massart noise (1)

Papers

Provable Uncertainty Decomposition via Higher-Order Calibration ICLR 2025 An Efficient Tester-Learner for Halfspaces ICLR 2024 Agnostically Learning Single-Index Models using Omnipredictors NeurIPS 2023 Ambient Diffusion: Learning Clean Distributions from Corrupted Data NeurIPS 2023 Tester-Learners for Halfspaces: Universal Algorithms NeurIPS 2023 Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks NeurIPS 2022 Statistical-Query Lower Bounds via Functional Gradients NeurIPS 2020 Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent ICML 2020