654 results for "uber estimate" across all locations
Pro Tips on Dynamic Pricing
Uber is all about connecting you with a reliable ride, no matter when you need it. With our growing demand on XL, Black and the latest addition to the family – uberTaxi, we want to ensure that you get a car even at the busiest hours. Today we’re introducing our dynamic pricing model in Istanbul, which allows us to remain reliable at all times. Increased rates incentivize more driver partners to get on the roads and ensure those who need a ride won’t be left stranded. This means that our rates will float in real time with fluctuations in supply and demand.
Eastern Province Your Uber Has Officially Arrived !!
It’s official: uberX, Uber’s lower cost option, is now LIVE in the Eastern Province! You can now request uberX cars in Dammam, Khobar and Dhahran!!
Your ride to skiing the east
Discover Kochi
Whether you’re new to the city, still needing maps to find your way around, or an old-timer with a stock of stories about the good ol’ days in Kochi
HDNET: Exploiting HD Maps for 3D Object Detection
B. Yang, M. Liang, R. Urtasun
In this paper we show that High-Definition (HD) maps provide strong priors that can boost the performance and robustness of modern 3D object detectors. Towards this goal, we design a single stage detector that extracts geometric and semantic features from the HD maps. […] [PDF]
Conference on Robot Learning (CORL), 2018
Lost Relatives of the Gumbel Trick
M. Balog, N. Tripuraneni, Z. Ghahramani, A. Weller
The Gumbel trick is a method to sample from a discrete probability distribution, or to estimate its normalizing partition function. The method relies on repeatedly applying a random perturbation to the distribution in a particular way, each time solving for the most likely configuration. […] [PDF]
International Conference on Machine Learning (ICML), 2017
Towards Diverse and Natural Image Descriptions via a Conditional GAN
B. Dai, S. Fidler, R. Urtasun, D. Lin
In this paper we introduce the TorontoCity benchmark, which covers the full greater Toronto area (GTA) with 712.5 km² of land, 8439 km of road and around 400,000 buildings. Our benchmark provides different perspectives of the world captured from airplanes, drones and cars driving around the city. […] [PDF]
International Conference on Computer Vision (ICCV), 2017
Mwongozo wa safari wakati wa Mkesha wa Mwaka Mpya wa 2018
Here are a few ways that Uber can help you start the new year with a reliable ride.
2018–19 New Year’s Eve ride guide
Here are a few ways that Uber can help you start the new year with a reliable ride.
From Nodes to Networks: Evolving Recurrent Neural Networks
A. Rawal, R. Miikkulainen
Gated recurrent networks such as those composed of Long Short-Term Memory (LSTM) nodes have recently been used to improve state of the art in many sequential processing tasks such as speech recognition and machine translation. However, the basic structure of the LSTM node is essentially the same as when it was first conceived 25 years ago. Recently, evolutionary and reinforcement learning mechanisms have been employed to create new variations of this structure. This paper proposes a new method, evolution of a tree-based encoding of the gated memory nodes, and shows that it makes it possible to explore new variations more effectively than other methods. […] [PDF at arXiv]
Workshop on Meta-Learning at Conference on Neural Information Processing Systems (MetaLearn @ NeurIPS), 2018