← Authors

Ameet Talwalkar

43 papers · 2009–2025 · 9 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (7) 🐝 Cross-Pollinator (13) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (16) πŸ—ΊοΈ Taxonomy Completionist (10) πŸ† Grand Slam πŸ‘‘ Triple Crown 🀝 Dynamic Duo (10) πŸ”¬ Deep Specialist (11) πŸ† Keyword Champion πŸ”₯ Unstoppable (8) πŸš€ Conference Pioneer ⚑ Prolific Year (8) πŸ—ƒοΈ Keyword Collector (148) ❓ The Questioner (2) πŸ’Ž Century Club (43) πŸ“ˆ Trend Setter

Conferences

NIPS (12) ICLR (9) AISTATS (6) ICML (6) JMLR (5) AAAI (2) ACL (1) ICCV (1) UAI (1)

Top co-authors

Mikhail Khodak (10) Valerie Chen (6) Liam Li (6) Mehryar Mohri (5) Gregory Plumb (5) Junhong Shen (4) Maria-Florina F Balcan (4) Misha Khodak (4) Graham Neubig (3) Sanjiv Kumar (3)

Keywords

hyperparameter optimization (6) low-rank approximation (5) neural architecture search (5) kernel methods (4) parallel computing (3) matrix factorization (3) transfer learning (3) model explanation (2) random search (2) post-hoc explanation (2) weight sharing (2) collaborative filtering (2) convolutional neural network (2) ensemble method (2) distributed computing (2) online learning (2) interpretable machine learning (2) federated learning (2) ridge regression (2) nystrom method (2)

Papers

Specialized Foundation Models Struggle to Beat Supervised Baselines ICLR 2025
Copilot Arena: A Platform for Code LLM Evaluation in the Wild ICML 2025
Learning Personalized Decision Support Policies AAAI 2025
When Benchmarks Talk: Re-Evaluating Code LLMs with Interactive Feedback ACL 2025
Understanding Optimization in Deep Learning with Central Flows ICLR 2025
On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods AAAI 2024
Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances ICLR 2024
AANG : Automating Auxiliary Learning ICLR 2023
Cross-Modal Fine-Tuning: Align then Refine ICML 2023
NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks NIPS 2022
Efficient Architecture Search for Diverse Tasks NIPS 2022
Provably tuning the ElasticNet across instances NIPS 2022
Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative ICLR 2022
Sanity Simulations for Saliency Methods ICML 2022
Use-Case-Grounded Simulations for Explanation Evaluation NIPS 2022
Learning Predictions for Algorithms with Predictions NIPS 2022
Bayesian Persuasion for Algorithmic Recourse NIPS 2022
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing NIPS 2021
A Learning Theoretic Perspective on Local Explainability ICLR 2021
Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability ICLR 2021
Geometry-Aware Gradient Algorithms for Neural Architecture Search ICLR 2021
Learning-to-learn non-convex piecewise-Lipschitz functions NIPS 2021
Rethinking Neural Operations for Diverse Tasks NIPS 2021
On Data Efficiency of Meta-learning AISTATS 2021
FACT: A Diagnostic for Group Fairness Trade-offs ICML 2020
Learning Fair Representations for Kernel Models AISTATS 2020
Regularizing Black-box Models for Improved Interpretability NIPS 2020
Explaining Groups of Points in Low-Dimensional Representations ICML 2020
Differentially Private Meta-Learning ICLR 2020
Random Search and Reproducibility for Neural Architecture Search UAI 2019
Provable Guarantees for Gradient-Based Meta-Learning ICML 2019
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization JMLR 2018
MLlib: Machine Learning in Apache Spark JMLR 2016
Non-stochastic Best Arm Identification and Hyperparameter Optimization AISTATS 2016
Supervised Neighborhoods for Distributed Nonparametric Regression AISTATS 2016
Distributed Matrix Completion and Robust Factorization JMLR 2015
Distributed Low-Rank Subspace Segmentation ICCV 2013
Large-scale SVD and Manifold Learning JMLR 2013
Sampling Methods for the NystrΓΆm Method JMLR 2012
Divide-and-Conquer Matrix Factorization NIPS 2011
Can matrix coherence be efficiently and accurately estimated? AISTATS 2011
On the Impact of Kernel Approximation on Learning Accuracy AISTATS 2010
Ensemble Nystrom Method NIPS 2009