1.1k citations · 1.9k across the 55 of their papers we have counts for
5 papers · 1 filter
Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations
Michael Laskey, Caleb Chuck, Jonathan Lee +5
Motivated by recent advances in Deep Learning for robot control, this paper considers two learning algorithms in terms of how they acquire demonstrations. "Human-Centric" (HC) samp…
Finite Sample Prediction and Recovery Bounds for Ordinal Embedding
Lalit Jain, Kevin Jamieson, Robert Nowak
The goal of ordinal embedding is to represent items as points in a low-dimensional Euclidean space given a set of constraints in the form of distance comparisons like "item is…
On the Detection of Mixture Distributions with applications to the Most Biased Coin Problem
Kevin Jamieson, Daniel Haas, Ben Recht
This paper studies the trade-off between two different kinds of pure exploration: breadth versus depth. The most biased coin problem asks how many total coin flips are required to…
Best-of-K Bandits
Max Simchowitz, Kevin Jamieson, Benjamin Recht
This paper studies the Best-of-K Bandit game: At each time the player chooses a subset S among all N-choose-K possible options and observes reward max(X(i) : i in S) where X is a r…
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
Lisha Li, Kevin Jamieson, Giulia DeSalvo +2
Performance of machine learning algorithms depends critically on identifying a good set of hyperparameters. While recent approaches use Bayesian optimization to adaptively select c…