2022 MSC Theses

• MSC-2022-01 Haviv Cohen (Roy Friedman, Nethanel Gelernter): Advanced UXSS Analysis
• MSC-2022-02 Eyal Mizrachi (Roy Schwartz): A Tight Approximation for Submodular Maximization with Mixed Packing and Covering Constraints
• MSC-2022-03 Eitan Kosman (Assaf Schuster, Ilya Kolchinsky): Complex Pattern Mining
• MSC-2022-04 Neta Dafni (Yuval FIlmus): Complexity measures on the symmetric group and beyond
• MSC-2022-05 Ido Imanuel (Ron Kimmel): Neural Algorithms for Precise Shape Completion
• MSC-2022-06 Koral Chapnik (Assaf Schuster, Ilya Kolchinsky): DARLING: Data-Aware Load Shedding in Complex Event Processing Systems
• MSC-2022-07 Evgenii Zheltonozhskii (Avi Mendelson , Alex Bronstein, Chaim Baskin): Reducing Supervision in Visual Recognition Tasks
• MSC-2022-08 Dan Kalifa (Kira Radinsky): Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly
• MSC-2022-09 Assaf Mauda (Michael Elad): Poisson Denoising of Images Using Deep Neural Networks Inspired by Classical Dictionary Based Algorithms
• MSC-2022-10 Maor Yankovitch (Assaf Schuster, Ilya Kolchinsky): HYPERSONIC: A Hybrid Parallelization Approach for Scalable Complex Event Processing
• MSC-2022-11 Sagi Levanon (Nir Rosenfeld): Generalized Strategic Classification and the Case of Aligned Incentives
• MSC-2022-12 Lior Ben-Yamin (Hadas Shachnai): Maximizing Throughput in Flow Shop Real-time Scheduling
• MSC-2022-13 Omer Dahary (Alex Bronstein): Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure Times
• MSC-2022-14 Majd Khalil (Benny Kimelfeld): The Complexity of the Shapley Value for Path Queries over Graphs
• MSC-2022-15 Boaz Ben-Dov (Roi Reichart): Predicting the Success of Domain Adaptation, a Casual Model Interpretation Approach
• MSC-2022-16 Adi Mesika (Ayellet Tal): CloudWalker: 3D Point Cloud Learning by Random Walks for Shape Analysis
• MSC-2022-17 Mohammed Dabbah (Ran El-yaniv): Using Fictitious Class Representations to Boost Discriminative Zero-Shot Learners
• MSC-2022-18 Elad Nachmias (Eran Yahav): Hierarchical Code Representations
• MSC-2022-19 Amir Livne (Ron Kimmel, Alex Bronstein): How to Avoid Depth Reconstruction in 3D Vision Tasks: Do We Need Depth in State-Of-The-Art Face Authentication?
• MSC-2022-20 Nir Diamant (Alexander Bronstein, Ehud Rivlin): Improving Real-World Data Generation using Adversarial Sim2Real Models
• MSC-2022-21 Guy Shapira (Assaf Schuster): Unsupervised Frequent Pattern Mining for CEP
• MSC-2022-22 Omer Antverg (Yonatan Belinkov): Investigating the Importance of Individual Neurons in Language Models
• MSC-2022-23 Alon Dankner (Eli Biham, Sara Bitan): Attacking and Securing ICS Protocols
• MSC-2022-24 Refael Cohen (Assaf Schuster): SMEGA2: Distributed Deep Learning Using a Single Momentum Buffer
• MSC-2022-25 Shadi Endrawis (Aviv Tamar): Efficient Self-Supervised Data Collection for Offline Robot Learning
• MSC-2022-26 Gal Sidi (Assaf Schuster, Ilya Kolchinsky): DELETE: Using deep learning to minimize latency in CEP systems
• MSC-2022-27 Tom Brand (Eli Ben-Sasson and Yuval Ishai): Bribery Attack on Nakamoto Consensus Proof of Stake Protocols