PhD and MSc Theses
PhD and MSc Theses, since 1988
Student's Name |
Graduation Year |
Degree |
Abstracts |
Research Name |
Giladi Niv |
2024 |
PhD |
Abstracts |
Enabling Scalable Learning with Large Models |
Greenberg-Toledo Tzofnat |
2024 |
PhD |
|
Analog Processing-In-Memory of Deep Neural Networks |
Hubara Itay |
2023 |
PhD |
Abstracts |
Towards Fast and Efficient Deep Learning |
Chmiel Brian |
2023 |
PhD |
Abstracts |
Resource Efficient Training and Inference in Deep Neural Networks |
Moroshko Edward |
2021 |
PhD |
Abstracts |
On Implicit Bias in Deep Models and Constrained Feedback in Online Learning |
Hoffer Elad |
2019 |
PhD |
Abstracts |
Deep Learning: Rethinking Common Practices |
Katz Itamar |
2019 |
PhD |
Abstracts |
Representation Learning via Clustering and Hierarchical Structures |
Evron Itay |
2019 |
MSc |
Abstracts |
Efficient Loss-Based Decoding on Graphs for Extreme Classification |
Gottlieb Shahar |
2024 |
MSc |
Abstracts |
Accelerating Distributed Training by Reducing Compute Time Variance |
Ben Uri Liad |
2022 |
MSc |
Abstracts |
Improving Efficiency of DNN Training using Stochastic Pruning |
Golan Itay |
2021 |
MSc |
Abstracts |
Effects of Human-Controlled Hyper-Parameters in Deep Neural Networks |
Zeno Chen |
2019 |
MSc |
Abstracts |
Task Agnostic Continual Learning using Online Variational Bayes |