5 citations · 20 across the 10 of their papers we have counts for
10 papers
Chronic Stress, Immune Suppression, and Cancer Occurrence: Unveiling the Connection using Survey Data and Predictive Models
Teddy Lazebnik, Vered Aharonson
Chronic stress was implicated in cancer occurrence, but a direct causal connection has not been consistently established. Machine learning and causal modeling offer opportunities t…
Accelerating Reinforcement Learning Algorithms Convergence using Pre-trained Large Language Models as Tutors With Advice Reusing
Lukas Toral, Teddy Lazebnik
Reinforcement Learning (RL) algorithms often require long training to become useful, especially in complex environments with sparse rewards. While techniques like reward shaping an…
Spatio-Temporal SIR Model of Pandemic Spread During Warfare with Optimal Dual-use Healthcare System Administration using Deep Reinforcement Learning
Adi Shuchami, Teddy Lazebnik
Large-scale crises, including wars and pandemics, have repeatedly shaped human history, and their simultaneous occurrence presents profound challenges to societies. Understanding t…
Mathematical model of dating apps influence on sexually transmitted diseases spread
Teddy Lazebnik
Sexually transmitted diseases (STDs) are a group of pathogens infecting new hosts through sexual interactions. Due to its social and economic burden, multiple models have been prop…
Machine Learning Approaches to Predict and Detect Early-Onset of Digital Dermatitis in Dairy Cows using Sensor Data
Jennifer Magana, Dinu Gavojdian, Yakir Menachem +3
The aim of this study was to employ machine learning algorithms based on sensor behavior data for (1) early-onset detection of digital dermatitis (DD); and (2) DD prediction in dai…
Digitally-Enhanced Dog Behavioral Testing: Getting Help from the Machine
Nareed Farhat, Teddy Lazebnik, Joke Monteny +4
The assessment of behavioral traits in dogs is a well-studied challenge due to its many practical applications such as selection for breeding, prediction of working aptitude, chanc…
BovineTalk: Machine Learning for Vocalization Analysis of Dairy Cattle under Negative Affective States
Dinu Gavojdian, Teddy Lazebnik, Madalina Mincu +3
There is a critical need to develop and validate non-invasive animal-based indicators of affective states in livestock species, in order to integrate them into on-farm assessment p…
Can We Mathematically Spot Possible Manipulation of Results in Research Manuscripts Using Benford's Law?
Teddy Lazebnik, Dan Gorlitsky
The reproducibility of academic research has long been a persistent issue, contradicting one of the fundamental principles of science. What is even more concerning is the increasin…
Break a Lag: Triple Exponential Moving Average for Enhanced Optimization
Roi Peleg, Yair Smadar, Teddy Lazebnik +1
The performance of deep learning models is critically dependent on sophisticated optimization strategies. While existing optimizers have shown promising results, many rely on first…
Cost-optimal Seeding Strategy During a Botanical Pandemic in Domesticated Fields
Teddy Lazebnik
Botanical pandemics cause enormous economic damage and food shortages around the globe. However, since botanical pandemics are here to stay in the short-medium term, domesticated f…