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01/24/2023
K-Planes: Explicit Radiance Fields in Space, Time, and Appearance
We introduce k-planes, a white-box model for radiance fields in arbitrar...
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08/01/2022
Towards Psychologically-Grounded Dynamic Preference Models
Designing recommendation systems that serve content aligned with time va...
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12/09/2021
Plenoxels: Radiance Fields without Neural Networks
We introduce Plenoxels (plenoptic voxels), a system for photorealistic v...
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12/02/2021
A note on sampling biases in the Bangladesh mask trial
A recent cluster trial in Bangladesh randomized 600 villages into 300 tr...
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06/30/2021
Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability
In this work, we consider how preference models in interactive recommend...
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03/05/2021
Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data
Collecting more diverse and representative training data is often touted...
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02/10/2021
Patterns, predictions, and actions: A story about machine learning
This graduate textbook on machine learning tells a story of how patterns...
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01/28/2021
Interpolating Classifiers Make Few Mistakes
This paper provides elementary analyses of the regret and generalization...
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11/21/2020
Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty
Modern nonlinear control theory seeks to endow systems with properties s...
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11/07/2020
Do Offline Metrics Predict Online Performance in Recommender Systems?
Recommender systems operate in an inherently dynamical setting. Past rec...
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10/30/2020
Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions
Modern nonlinear control theory seeks to develop feedback controllers th...
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10/16/2020
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery
Combining satellite imagery with machine learning (SIML) has the potenti...
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08/27/2020
Certainty Equivalent Perception-Based Control
In order to certify performance and safety, feedback control requires pr...
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07/10/2020
Finding Equilibrium in Multi-Agent Games with Payoff Uncertainty
We study the problem of finding equilibrium strategies in multi-agent ga...
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07/01/2020
Measuring Robustness to Natural Distribution Shifts in Image Classification
We study how robust current ImageNet models are to distribution shifts a...
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06/18/2020
Active Learning for Nonlinear System Identification with Guarantees
While the identification of nonlinear dynamical systems is a fundamental...
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04/29/2020
The Effect of Natural Distribution Shift on Question Answering Models
We build four new test sets for the Stanford Question Answering Dataset ...
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03/12/2020
Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information
Observational data are often accompanied by natural structural indices, ...
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03/04/2020
Neural Kernels Without Tangents
We investigate the connections between neural networks and simple buildi...
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12/20/2019
Recommendations and User Agency: The Reachability of Collaboratively-Filtered Information
Recommender systems often rely on models which are trained to maximize a...
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07/08/2019
Robust Guarantees for Perception-Based Control
Motivated by vision based control of autonomous vehicles, we consider th...
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06/05/2019
A systematic framework for natural perturbations from videos
We introduce a systematic framework for quantifying the robustness of cl...
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05/30/2019
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator
We study the sample complexity of approximate policy iteration (PI) for ...
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05/29/2019
Model Similarity Mitigates Test Set Overuse
Excessive reuse of test data has become commonplace in today's machine l...
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02/21/2019
Certainty Equivalent Control of LQR is Efficient
We study the performance of the certainty equivalent controller on the L...
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02/02/2019
Learning Linear Dynamical Systems with Semi-Parametric Least Squares
We analyze a simple prefiltered variation of the least squares estimator...
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12/09/2018
The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint
The effectiveness of model-based versus model-free methods is a long-sta...
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10/23/2018
numpywren: serverless linear algebra
Linear algebra operations are widely used in scientific computing and ma...
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10/13/2018
Massively Parallel Hyperparameter Tuning
Modern learning models are characterized by large hyperparameter spaces....
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09/28/2018
Minimax Lower Bounds for H_∞-Norm Estimation
The problem of estimating the H_∞-norm of an LTI system from noisy input...
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09/27/2018
A Successive-Elimination Approach to Adaptive Robotic Sensing
We study the adaptive sensing problem for the multiple source seeking pr...
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09/26/2018
Safely Learning to Control the Constrained Linear Quadratic Regulator
We study the constrained linear quadratic regulator with unknown dynamic...
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06/25/2018
A Tour of Reinforcement Learning: The View from Continuous Control
This manuscript surveys reinforcement learning from the perspective of o...
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06/01/2018
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
Machine learning is currently dominated by largely experimental work foc...
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05/23/2018
Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator
We consider adaptive control of the Linear Quadratic Regulator (LQR), wh...
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04/04/2018
Tight Query Complexity Lower Bounds for PCA via Finite Sample Deformed Wigner Law
We prove a query complexity lower bound for approximating the top r dime...
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03/25/2018
Finite-Data Performance Guarantees for the Output-Feedback Control of an Unknown System
As the systems we control become more complex, first-principle modeling ...
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03/19/2018
Simple random search provides a competitive approach to reinforcement learning
A common belief in model-free reinforcement learning is that methods bas...
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02/22/2018
Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification
We prove that the ordinary least-squares (OLS) estimator attains nearly ...
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12/22/2017
Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator
Reinforcement learning (RL) has been successfully used to solve many con...
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11/15/2017
An example of how false conclusions could be made with personalized health tracking and suggestions for avoiding similar situations
Personalizing interventions and treatments is a necessity for optimal me...
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10/25/2017
Ground Control to Major Tom: the importance of field surveys in remotely sensed data analysis
In this project, we build a modular, scalable system that can collect, s...
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10/20/2017
First-order Methods Almost Always Avoid Saddle Points
We establish that first-order methods avoid saddle points for almost all...
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10/04/2017
On the Sample Complexity of the Linear Quadratic Regulator
This paper addresses the optimal control problem known as the Linear Qua...
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08/03/2017
Flare Prediction Using Photospheric and Coronal Image Data
The precise physical process that triggers solar flares is not currently...
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07/19/2017
Meaningless comparisons lead to false optimism in medical machine learning
A new trend in medicine is the use of algorithms to analyze big datasets...
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05/23/2017
The Marginal Value of Adaptive Gradient Methods in Machine Learning
Adaptive optimization methods, which perform local optimization with a m...
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04/14/2017
On the Gap Between Strict-Saddles and True Convexity: An Omega(log d) Lower Bound for Eigenvector Approximation
We prove a query complexity lower bound on rank-one principal component ...
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02/16/2017
The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime
We propose a novel technique for analyzing adaptive sampling called the ...
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09/21/2016
