← Authors

Gregory Valiant

35 papers · 2013–2023 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (10) 🐝 Cross-Pollinator (5) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (50) 🌱 Topic Pioneer πŸ† Keyword Champion πŸ—ƒοΈ Keyword Collector (179) πŸ’Ž Century Club (35) πŸ“ˆ Trend Setter ❓ The Questioner πŸ”₯ Unstoppable (11) ⚑ Prolific Year (6)

Conferences

NIPS (12) ICML (11) COLT (7) AISTATS (2) ACL (1) IJCAI (1) IJCNLP (1)

Top co-authors

Vatsal Sharan (8) Weihao Kong (4) Percy Liang (4) Annie Marsden (4) Paul Valiant (3) Shivam Garg (3) Kai Sheng Tai (3) Aaron Sidford (3) Sham Kakade (2) Chuma Kabaghe (2)

Research topics

Statistics (1)

Keywords

convex optimization (4) statistical estimation (4) parameter estimation (3) sample complexity (3) gradient descent (3) first-order method (2) sublinear sample (2) earth mover distance (2) audio perception (2) image classification (2) distribution learning (2) linear regression (2) sublinear sampling (2) spectral method (2) feature learning (2) population estimation (2) in-context learning (2) learning theory (2) query complexity (2) polyperceivable audio (2)

Papers

One-sided Matrix Completion from Two Observations Per Row ICML 2023
Lexinvariant Language Models NIPS 2023
Efficient Convex Optimization Requires Superlinear Memory (Extended Abstract) IJCAI 2023
Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales COLT 2022
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes NIPS 2022
Efficient Convex Optimization Requires Superlinear Memory COLT 2022
Exponential Weights Algorithms for Selective Learning COLT 2021
Beyond Laurel/Yanny: An Autoencoder-Enabled Search for Polyperceivable Audio ACL 2021
Beyond Laurel/Yanny: An Autoencoder-Enabled Search for Polyperceivable Audio IJCNLP 2021
Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training ICML 2021
Misspecification in Prediction Problems and Robustness via Improper Learning AISTATS 2021
On the Generalization Effects of Linear Transformations in Data Augmentation ICML 2020
Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process COLT 2020
Worst-Case Analysis for Randomly Collected Data NIPS 2020
Sublinear Optimal Policy Value Estimation in Contextual Bandits AISTATS 2020
Sample Amplification: Increasing Dataset Size even when Learning is Impossible ICML 2020
A Theory of Selective Prediction COLT 2019
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families NIPS 2019
Making AI Forget You: Data Deletion in Machine Learning NIPS 2019
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data ICML 2019
Equivariant Transformer Networks ICML 2019
Maximum Likelihood Estimation for Learning Populations of Parameters ICML 2019
A Spectral View of Adversarially Robust Features NIPS 2018
Estimating Learnability in the Sublinear Data Regime NIPS 2018
A Data Prism: Semi-verified learning in the small-alpha regime COLT 2018
Learning Populations of Parameters NIPS 2017
Learning Overcomplete HMMs NIPS 2017
Estimating the unseen from multiple populations ICML 2017
Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use ICML 2017
Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction NIPS 2016
Memory, Communication, and Statistical Queries COLT 2016
Testing Closeness With Unequal Sized Samples NIPS 2015
Least Squares Revisited: Scalable Approaches for Multi-class Prediction ICML 2014
Learning Polynomials with Neural Networks ICML 2014
Estimating the Unseen: Improved Estimators for Entropy and other Properties NIPS 2013