no code implementations • 5 Jan 2021 • Daniel Ben David, Yehezkel S. Resheff, Talia Tron
We study whether receiving advice from either a human or algorithmic advisor, accompanied by five types of Local and Global explanation labelings, has an effect on the readiness to adopt, willingness to pay, and trust in a financial AI consultant.
no code implementations • 7 Aug 2019 • Yair Horesh, Noa Haas, Elhanan Mishraky, Yehezkel S. Resheff, Shir Meir Lador
As AI systems develop in complexity it is becoming increasingly hard to ensure non-discrimination on the basis of protected attributes such as gender, age, and race.
no code implementations • 10 Jul 2018 • Yehezkel S. Resheff, Yanai Elazar, Moni Shahar, Oren Sar Shalom
Latent factor models for recommender systems represent users and items as low dimensional vectors.
no code implementations • 19 Dec 2017 • Yehezkel S. Resheff, Moni Shahar
Inferring user characteristics such as demographic attributes is of the utmost importance in many user-centric applications.
1 code implementation • 20 Apr 2017 • Yehezkel S. Resheff, Amit Mandelbaum, Daphna Weinshall
Deep learning has become the method of choice in many application domains of machine learning in recent years, especially for multi-class classification tasks.
no code implementations • 24 Jul 2016 • Yehezkel S. Resheff
Trajectory segmentation is the process of subdividing a trajectory into parts either by grouping points similar with respect to some measure of interest, or by minimizing a global objective function.
no code implementations • 17 Nov 2015 • Yehezkel S. Resheff, Daphna Weinshall
Since most data analysis and statistical methods do not handle gracefully missing values, the first step in the analysis requires the imputation of missing values.
no code implementations • 16 Nov 2015 • Yehezkel S. Resheff, Shay Rotics, Ran Nathan, Daphna Weinshall
A common use of accelerometer data is for supervised learning of behavioral modes.