About

The Machine Learning for Health and Well-Being (MLwell) Lab is a research lab at the Bio-Medical Engineering department at Tel-Aviv University. Our vision is to create the technology to allow everyone and everywhere access to personalized medicine and precision psychology that is: (i) effective (ii) respects the biological, cultural and behavioral differences between people (iii) respects privacy and other ethical requirements (iv) affordable. Our mission is to improve the state in the art in machine learning algorithms for personalized medicine and precision psychology.

Our News

Announcement

MLwell lab to receive support from the Israel Science Foundation

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The Israel Science Foundation has announced that it will support our research on "Explainable Learning on Graphs and Sets" for 3 years. We are very thankful and eager to work on this topic with this great support.

Upcoming Event

1st Data-Government conference

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Ran Gilad-Bachrach will deliver a short talk as a part of the 1st Data-Government conference in Israel in the Reichman University,

Announcement

Clean up your datasets with dftest

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Read the blog post of Atai Ambus on our new tool, dftest, for unit-testing data. This is our contribution to the data centric AI field.

New Paper

A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits

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When interacting with humans, boredom/novelty should be considered when selecting content. In this paper, recently presented at AIstats we present a novel version of the multi-armed bandit problem that defines this problem. We present theoretical analysis of the problem and algorithms.

New Paper

PyBryt: auto-assessment and auto-grading for computational thinking

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In a new technical report we introduce a new tool for auto-grading and auto-assessment to support the learning of computations thinking skills

Announcement

Congratulations to Amnon Catav for defending his thesis

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Congratulations to Amnon Catav for successfully defending his Master's thesis

New Paper

Break your Bandit Routine with LSD Rewards: a Last Switch Dependent Analysis of Satiation and Seasonality

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In a new technical report we discuss a version of the multi-armed bandit problem that is designed to delivering interventions to people and takes into account novelty effects.

Announcement

Congratulations to Gon Shoham for defending his thesis

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Congratulations to Gon Shoham for successfully defending his Master's thesis

Announcement

Congratulations to Roy Hirsch for defending his thesis

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Congratulations to Roy Hirsch for successfully defending his Master's thesis

Announcement

Congratulations to Omri Armstrong for defending his thesis

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Congratulations to Omri Armstrong for successfully defending his Master's thesis

New Paper

Marginal Contribution Feature Importance-an Axiomatic Approach for Explaining Data

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The paper studies way to assign feature importance in order to gain insights about data appeared in ICML 2021

New Paper

Trees with Attention for Set Prediction Tasks

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In a new ICML 2021 paper we shows how decision trees can be applied to data with sets. Empirical results show it is on par and sometimes outperforms deep learning.