← Authors

Vatsal Sharan

26 papers · 2017–2026 · 8 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (9) 🌈 Renaissance Researcher (6) 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (39) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (8) πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ”₯ Unstoppable (9) ⚑ Prolific Year (8) πŸ’Ž Century Club (25) ❓ The Questioner (3) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (108)

Conferences

NIPS (9) ICML (5) COLT (4) AISTATS (2) ALT (2) ICLR (2) AAAI (1) IJCAI (1)

Top co-authors

Siddartha Devic (8) Gregory Valiant (8) Julian Asilis (4) Shaddin Dughmi (4) Shang-Hua Teng (4) Aleksandra Korolova (3) Deqing Fu (3) David Kempe (3) Parikshit Gopalan (3) Udi Wieder (3)

Keywords

convex optimization (3) learning theory (2) empirical risk minimization (2) multiclass classification (2) spectral method (2) transductive learning (2) anomaly detection (2) query complexity (2) calibration error (2) algorithmic fairness (2) non-convex optimization (1) density estimation (1) parameter estimation (1) mathematical reasoning (1) online learning (1) feature learning (1) compressive sensing (1) pac learning (1) principal component analysis (1) sample complexity (1)

Papers

An External Fairness Evaluation of LinkedIn Talent Search AAAI 2026
Transformers Learn Low Sensitivity Functions: Investigations and Implications ICLR 2025
Proper Learnability and the Role of Unlabeled Data ALT 2025
On the Inherent Privacy of Zeroth-Order Projected Gradient Descent AISTATS 2025
Optimal Multiclass U-Calibration Error and Beyond NIPS 2024
Pre-trained Large Language Models Use Fourier Features to Compute Addition NIPS 2024
When is Multicalibration Post-Processing Necessary? NIPS 2024
Transductive Learning is Compact NIPS 2024
Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression NIPS 2024
Regularization and Optimal Multiclass Learning COLT 2024
Open Problem: Can Local Regularization Learn All Multiclass Problems? COLT 2024
Stability and Multigroup Fairness in Ranking with Uncertain Predictions ICML 2024
Fairness in Matching under Uncertainty ICML 2023
Efficient Convex Optimization Requires Superlinear Memory (Extended Abstract) IJCAI 2023
Efficient Convex Optimization Requires Superlinear Memory COLT 2022
Multicalibrated Partitions for Importance Weights ALT 2022
Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales COLT 2022
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks ICLR 2021
Sample Amplification: Increasing Dataset Size even when Learning is Impossible ICML 2020
Recovery Guarantees For Quadratic Tensors With Sparse Observations AISTATS 2019
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data ICML 2019
PIDForest: Anomaly Detection via Partial Identification NIPS 2019
A Spectral View of Adversarially Robust Features NIPS 2018
Efficient Anomaly Detection via Matrix Sketching NIPS 2018
Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use ICML 2017
Learning Overcomplete HMMs NIPS 2017