2055 results for "receipt" across all locations
New Pickup & Drop Off locations at Chadstone Shopping Centre
To make pickups at Chadstone Shopping Centre easier we’ve partnered with them to create dedicated Uber pickup and dropoff locations at specific locati
Ride to give back with Banner Health
Earn Uber Credit!
We want to make it even easier for you to earn more FREE rides! We’re excited to offer an exclusive Chicago promotion to refer your friends to DRIVE with Uber.
Presenting the new Uber Ambassador program
UberSERENADE Terms and Conditions
Uber Eats at Dodger Stadium
In 2024, fans at Dodger Stadium can order food and beverages for fast pickup directly from the Uber Eats app. When at Dodger Stadium, you can open your Uber Eats app, select the location you’re in, and you will be shown all available merchants you can order from. When the order is ready, you will receive a notification to skip the line and pick it up, so you don’t have to spend time waiting in lines and risk missing any of the game
Face Mask Collections at Dekra
Uber and Dekra South Africa have partnered to distribute masks to driver-partners. The masks are made by the Youth Employment Service, a nonprofit organisation, that supports unemployed youth in South Africa. The masks are made from fabric and are washable, therefore making them reusable. Qualifying driver-partners will receive two masks, at no cost to them, so that they can wear one while washing the other.
The Mirage of Action-Dependent Baselines in Reinforcement Learning
G. Tucker, S. Bhupatiraju, S. Gu, R. Turner, Z. Ghahramani, S. Levine
Policy gradient methods are a widely used class of model-free reinforcement learning algorithms where a state-dependent baseline is used to reduce gradient estimator variance. Several recent papers extend the baseline to depend on both the state and action and suggest that this significantly reduces variance and improves sample efficiency without introducing bias into the gradient estimates. […] [PDF]
International Conference on Machine Learning (ICML), 2018
Bayesian inference on random simple graphs with power law degree distributions
J. Lee, C. Heaukulani, Z. Ghahramani, L. James, S. Choi
We present a model for random simple graphs with a degree distribution that obeys a power law (i.e., is heavy-tailed). To attain this behavior, the edge probabilities in the graph are constructed from Bertoin-Fujita-Roynette-Yor (BFRY) random variables, which have been recently utilized in Bayesian statistics for the construction of power law models in several applications. […] [PDF]
International Conference on Machine Learning (ICML), 2017