2270 results for "earn" across all locations
Manifold: A Model-Agnostic Visual Debugging Tool for Machine Learning at Uber
Uber built Manifold, a model-agnostic visualization tool for ML performance diagnosis and model debugging, to facilitate a more informed and actionable model iteration process.
Learning Continuous Treatment Policy and Bipartite Embeddings for Matching with Heterogeneous Causal Effects
W. Y. Zou, S. Shyam, M. Mui, M. Wang, J. Pedersen, Z. Ghahramani
Causal inference methods are widely applied in the fields of medicine, policy, and economics. Central to these applications is the estimation of treatment effects to make decisions. Current methods make binary yes-or-no decisions based on the treatment effect of a single outcome dimension. These methods are unable to capture continuous space treatment policies with a measure of intensity. […] [PDF]
2020
Learning a Generative Model for Multi-Step Human-Object Interactions from Videos
H. Wang, S. Pirk, V. Kim, E. Yumer, L. Guibas
Creating dynamic virtual environments consisting of humans interacting with objects is a fundamental problem in computer graphics. While it is well-accepted that agent interactions play an essential role in synthesizing such scenes, most extant techniques exclusively focus on static scenes, leaving the dynamic component out. In this paper, we present a generative model to synthesize plausible multi-step dynamic human–object interactions. […] [PDF]
European Association for Computer Graphics (Eurographics), 2019
Art, culture and history in Port Elizabeth, the jewel of Nelson Mandela Bay
Most may know it today as a city with popular beaches and beautiful, natural surroundings, there’s more history and culture than meets the eye.
New Facility Insights Report presents key learnings to shippers
Our first Facility Insights Report is a crucial step towards marketwide transparency.
Five Key Learnings from Uber’s Leadership Panel on the Power of Visibility
To celebrate International Women’s Day, we hosted a panel of leaders from across Uber showcasing the power of visibility. Ana Loibner, Global Mobility Chief of Staff and Women at Uber Global Board Member, shares what she learned.
They helped move the world. Learn how they can help your team.
Danielle Monaghan, Vice President, Global Head of Talent Acquisition shares our Talent Directory and why companies should reach out to those profiled.
Meta-Graph: Few-Shot Link Prediction Using Meta-Learning
Uber AI introduces Meta-Graph, a new few-shot link prediction framework that facilitates the more accurate training of ML models that quickly adapt to new graph data.
IntentNet: Learning to Predict Intention from Raw Sensor Data
S. Casas, W. Luo, R. Urtasun
In order to plan a safe maneuver, self-driving vehicles need to understand the intent of other traffic participants. We define intent as a combination of discrete high level behaviors as well as continuous trajectories describing future motion. In this paper we develop a one-stage detector and forecaster that exploits both 3D point clouds produced by a LiDAR sensor as well as dynamic maps of the environment. […] [PDF]
Conference on Robot Learning (CORL), 2018
Model Excellence Scores: A Framework for Enhancing the Quality of Machine Learning Systems at Scale
With the introduction of Model Excellence Scores at Uber, we’re setting a new standard for measuring, monitoring, and maintaining ML model quality–read how this innovative approach aims to enhance ML governance and provide clearer insights.