← Authors

Benjamin Recht

44 papers · 2007–2025 · 11 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (18) 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (11) πŸ—ΊοΈ Taxonomy Completionist (17) 🐝 Cross-Pollinator (5) 🌱 Topic Pioneer πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (56) πŸ’Ž Century Club (44) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (9) ⚑ Prolific Year (7) ❓ The Questioner (2)

Conferences

NIPS (13) ICML (9) COLT (7) JMLR (6) CVPR (2) L4DC (2) AISTATS (1) CORL (1) ICCV (1) NAACL (1) NSDI (1)

Top co-authors

Ludwig Schmidt (8) Horia Mania (7) Michael I. Jordan (7) Stephen Tu (7) Vaishaal Shankar (6) Rebecca Roelofs (5) Max Simchowitz (5) Sarah Dean (5) Sara Fridovich-Keil (4) Moritz Hardt (3)

Keywords

sample complexity (6) linear quadratic regulator (5) stochastic gradient descent (4) regret bound (3) autonomous vehicle (3) image classification (3) system identification (3) linear dynamical system (3) distribution shift (3) optimal control (3) reinforcement learning (2) policy evaluation (2) generalization bound (2) random feature (2) pure exploration (2) sparse optimization (2) benchmark evaluation (2) kernel approximation (2) continuous control (2) multi-armed bandit (2)

Papers

From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms ICML 2025
Interpolating Classifiers Make Few Mistakes JMLR 2023
K-Planes: Explicit Radiance Fields in Space, Time, and Appearance CVPR 2023
Plenoxels: Radiance Fields Without Neural Networks CVPR 2022
Active Learning for Nonlinear System Identification with Guarantees JMLR 2022
Certainty Equivalent Perception-Based Control L4DC 2021
Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data ICML 2021
Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability ICML 2021
Do Image Classifiers Generalize Across Time? ICCV 2021
Evaluating Machine Accuracy on ImageNet ICML 2020
The Effect of Natural Distribution Shift on Question Answering Models ICML 2020
Robust Guarantees for Perception-Based Control L4DC 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification NIPS 2020
Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions CORL 2020
Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information AISTATS 2020
Neural Kernels Without Tangents ICML 2020
Do ImageNet Classifiers Generalize to ImageNet? ICML 2019
Model Similarity Mitigates Test Set Overuse NIPS 2019
Certainty Equivalence is Efficient for Linear Quadratic Control NIPS 2019
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator NIPS 2019
A Meta-Analysis of Overfitting in Machine Learning NIPS 2019
Learning Linear Dynamical Systems with Semi-Parametric Least Squares COLT 2019
The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint COLT 2019
Towards augmenting crisis counselor training by improving message retrieval NAACL 2019
Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator NIPS 2018
Simple random search of static linear policies is competitive for reinforcement learning NIPS 2018
Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator ICML 2018
Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification COLT 2018
Gradient Descent Learns Linear Dynamical Systems JMLR 2018
Saturating Splines and Feature Selection JMLR 2018
The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime COLT 2017
Breaking Locality Accelerates Block Gauss-Seidel ICML 2017
The Marginal Value of Adaptive Gradient Methods in Machine Learning NIPS 2017
Ernest: Efficient Performance Prediction for Large-Scale Advanced Analytics NSDI 2016
Gradient Descent Only Converges to Minimizers COLT 2016
Best-of-K-bandits COLT 2016
The Power of Adaptivity in Identifying Statistical Alternatives NIPS 2016
Parallel Correlation Clustering on Big Graphs NIPS 2015
The Randomized Causation Coefficient JMLR 2015
Toward a Noncommutative Arithmetic-geometric Mean Inequality: Conjectures, Case-studies, and Consequences COLT 2012
Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NIPS 2011
A Simpler Approach to Matrix Completion JMLR 2011
Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning NIPS 2008
Random Features for Large-Scale Kernel Machines NIPS 2007