2052 results for "receipt" across all locations
Valentine’s Day driver stories
Drivers share their memorable on-the-road moments.
Uber’s impact on Taxi Crime in Chicago
Taxicabs have been the venue for thousands of crimes committed in Chicago in the last decade. However, Uber’s entrance into Chicago has shown a favorable correlation with the decline of taxi crime rates.
Uber, the official ride of the AFL
If you’re choosing to revel in footy fever over weekend, leave the car behind and plan ahead with Uber.
Keep riding to unlock promocodes
Take 2 Uber rides before Wednesday 14 June 2017 and unlock a discount promocode for 4 Uber rides. Ride now!
Stay connected at the railway station
Juggling our different commitments in our 24/7 world can be tough. Thankfully, staying connected while travelling to or from Delhi NCR just got easier
Postmates x Bludso’s 2023 Sweepstakes Official Rules
Postmates, LLC (“Postmates”) is sponsoring the Postmates x Bludsos 2023 Sweepstakes (the “Sweepstakes”). The Sweepstakes is subject to these official rules (the “Official Rules”), and by participating, you (“Entrant”) agree to be bound by them and the decisions of Postmates, which are final and binding in all respects.
NO PURCHASE OR ORDER NECESSARY TO ENTER OR WIN A PRIZE. A PURCHASE DOES NOT IMPROVE YOUR CHANCES OF WINNING. ODDS OF WINNING WILL DEPEND ON THE TOTAL NUMBER OF ELIGIBLE ENTRIES RECEIVED. VOID WHERE PROHIBITED BY LAW OR RESTRICTED BY LAW.
Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models
J. Zhang, Y. Wang, P. Molino, L. Li, D. Ebert
Interpretation and diagnosis of machine learning models have gained renewed interest in recent years with breakthroughs in new approaches. We present Manifold, a framework that utilizes visual analysis techniques to support interpretation, debugging, and comparison of machine learning models in a more transparent and interactive manner. […] [PDF]
IEEE Visualization (IEEE VIS), 2018
Learning deep structured active contours end-to-end
D. Marcos, D. Tuia, B. Kellenberger, L. Zhang, M. Bai, R. Liao, R. Urtasun
The world is covered with millions of buildings, and precisely knowing each instance’s position and extents is vital to a multitude of applications. Recently, automated building footprint segmentation models have shown superior detection accuracy thanks to the usage of Convolutional Neural Networks (CNN). […] [PDF]
Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Measuring the Intrinsic Dimension of Objective Landscapes
Chunyuan Li, Heerad Farkhoor, R. Liu, J. Yosinski
Many recently trained neural networks employ large numbers of parameters to achieve good performance. One may intuitively use the number of parameters required as a rough gauge of the difficulty of a problem. But how accurate are such notions? How many parameters are really needed? In this paper we attempt to answer this question by training networks not in their native parameter space, but instead in a smaller, randomly oriented subspace. […] [PDF]
International Conference on Learning Representations (ICLR), 2018
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
H. Zhou, J. Lan, R. Liu, J. Yosinski
Optical Character Recognition (OCR) approaches have been widely advanced in recent years thanks to the resurgence of deep learning. The state-of-the-art models are mainly trained on the datasets consisting of the constrained scenes. Detecting and recognizing text from the real-world images remains a technical challenge. […] [PDF]
Conference on Neural Information Processing Systems (NeurIPS), 2019