678 citations · 1.6k across the 28 of their papers we have counts for
10 papers · 1 filter
Robust Autonomy Emerges from Self-Play
Marco Cusumano-Towner, David Hafner, Alex Hertzberg +9
Self-play has powered breakthroughs in two-player and multi-player games. Here we show that self-play is a surprisingly effective strategy in another domain. We show that robust an…
Leveraging Cardiovascular Simulations for In-Vivo Prediction of Cardiac Biomarkers
Laura Manduchi, Antoine Wehenkel, Jens Behrmann +6
Whole-body hemodynamics simulators, which model blood flow and pressure waveforms as functions of physiological parameters, are now essential tools for studying cardiovascular syst…
Domain Generalization without Excess Empirical Risk
Ozan Sener, Vladlen Koltun
Given data from diverse sets of distinct distributions, domain generalization aims to learn models that generalize to unseen distributions. A common approach is designing a data-dr…
Generalizing Gaussian Smoothing for Random Search
Katelyn Gao, Ozan Sener
Gaussian smoothing (GS) is a derivative-free optimization (DFO) algorithm that estimates the gradient of an objective using perturbations of the current parameters sampled from a s…
Online Continual Learning with Natural Distribution Shifts: An Empirical Study with Visual Data
Zhipeng Cai, Ozan Sener, Vladlen Koltun
Continual learning is the problem of learning and retaining knowledge through time over multiple tasks and environments. Research has primarily focused on the incremental classific…
Modeling and Optimization Trade-off in Meta-learning
Katelyn Gao, Ozan Sener
By searching for shared inductive biases across tasks, meta-learning promises to accelerate learning on novel tasks, but with the cost of solving a complex bilevel optimization pro…
Drinking from a Firehose: Continual Learning with Web-scale Natural Language
Hexiang Hu, Ozan Sener, Fei Sha +1
Continual learning systems will interact with humans, with each other, and with the physical world through time -- and continue to learn and adapt as they do. An important open pro…
Learning to Guide Random Search
Ozan Sener, Vladlen Koltun
We are interested in derivative-free optimization of high-dimensional functions. The sample complexity of existing methods is high and depends on problem dimensionality, unlike the…
Multi-Task Learning as Multi-Objective Optimization
Ozan Sener, Vladlen Koltun
In multi-task learning, multiple tasks are solved jointly, sharing inductive bias between them. Multi-task learning is inherently a multi-objective problem because different tasks…
Deep Learning under Privileged Information Using Heteroscedastic Dropout
John Lambert, Ozan Sener, Silvio Savarese
Unlike machines, humans learn through rapid, abstract model-building. The role of a teacher is not simply to hammer home right or wrong answers, but rather to provide intuitive com…