19 citations · 27 across the 7 of their papers we have counts for
7 papers
Partitioning Israeli Municipalities into Politically Homogeneous Cantons: A Constrained Spatial Clustering Approach
Adir Elmakais, Oren Glickman
Israeli society has experienced significant political polarization in recent years, reflected in five Knesset elections held within a four-year period (2019-2022). Public discourse…
NER Retriever: Zero-Shot Named Entity Retrieval with Type-Aware Embeddings
Or Shachar, Uri Katz, Yoav Goldberg +1
We present NER Retriever, a zero-shot retrieval framework for ad-hoc Named Entity Retrieval, a variant of Named Entity Recognition (NER), where the types of interest are not provid…
Data Augmentation for Deep Learning Regression Tasks by Machine Learning Models
Assaf Shmuel, Oren Glickman, Teddy Lazebnik
Deep learning (DL) models have gained prominence in domains such as computer vision and natural language processing but remain underutilized for regression tasks involving tabular…
Global Lightning-Ignited Wildfires Prediction and Climate Change Projections based on Explainable Machine Learning Models
Assaf Shmuel, Teddy Lazebnik, Oren Glickman +2
Wildfires pose a significant natural disaster risk to populations and contribute to accelerated climate change. As wildfires are also affected by climate change, extreme wildfires…
A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
Assaf Shmuel, Oren Glickman, Teddy Lazebnik
The analysis of tabular datasets is highly prevalent both in scientific research and real-world applications of Machine Learning (ML). Unlike many other ML tasks, Deep Learning (DL…
Supervised Embedded Methods for Hyperspectral Band Selection
Yaniv Zimmer, Ofir Lindenbaum, Oren Glickman
Hyperspectral Imaging (HSI) captures rich spectral information across contiguous wavelength bands, supporting applications in precision agriculture, environmental monitoring, and a…
Symbolic Regression as Feature Engineering Method for Machine and Deep Learning Regression Tasks
Assaf Shmuel, Oren Glickman, Teddy Lazebnik
In the realm of machine and deep learning regression tasks, the role of effective feature engineering (FE) is pivotal in enhancing model performance. Traditional approaches of FE o…