Blockchain Loans: Mechanisms, Platforms And Challenges

Distributed lending protocols are major financial mechanisms that match borrowers and lenders without the need for intermediaries. Smart contracts deployed on blockchains ensure the security of such loans. Borrowers mitigate the risk of default by providing collateral in the form of cryptocurrencies or by limiting the loan duration.
In the first part of the talk, we describe various loan types, major platforms, and financial models that allow them. In the second part of the talk,...

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The Sky Is The Limit - An Open Day For Advanced Degree Studies At The Faculty

Wednesday, 22.05.2024, 13:00

Taub 337

A meeting of those interested in graduate studies at the Taub Faculty of Computer Science at the Technion will be held on Wednesday, May 22, 2024, 1:00 p.m., room 337
Outstanding bachelor's graduates from all universities!
This is your opportunity to participate and be impressed by the Faculty of Computer Science at the Technion, Meet faculty members and graduate students and hear fascinating lectures.
To participate, please register in advance at the ...

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Pixel Club: Deep Computational Imaging: Optimal sensing, reconstruction, and uncertainty quantification

Elias Nehme - The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering

Tuesday, 16.04.2024, 14:30

Room 1061, EE Meyer Building & Zoom Lecture:5049603009

In biological imaging, fast acquisition of depth information is crucial e.g. for accurate 3D tracking of sub-cellular elements and for 3D super-resolution. In the first part of this talk, we present a series of works enhancing the success of snapshot depth sensing in the revolutionary field of single-molecule localization microscopy (Nobel Prize in Chemistry 2014). Specifically, we present an approach for jointly designing the “optics” of the microscope and the 3D reconstructi...

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Deep Learning and Tree Search-Based Policy Optimization under Stochastic Execution Delay

The standard formulation of Markov decision processes (MDPs) assumes that the agent's decisions are executed immediately. However, in numerous realistic applications such as robotics or healthcare, actions are performed with a delay whose value can even be stochastic. In this work, we introduce stochastic delayed execution MDPs, a new formalism addressing random delays without resorting to state augmentation. We show that given observed delay values, it is sufficient to perform a ...

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A VIP Visit At The Technion For Children Of Graduates

Monday, 15.04.2024, 10:00

Technion, Ulman Building

Graduates of the faculty are invited with their children to a day of lectures, workshops and information regarding registration and admission - for children; and a nostalgic tour (for parents)
Monday, April 15, starting at 10:00 at the Technion
In the program:
1. The wonders of infinity - the Faculty of Mathematics
2. What is the Internet of Things? - Faculty of Computer Science
3. Games and Virtual Reality - Fac...

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CE-Club: Buffer Isolation With Imperfect Congestion Control Classification

Due to their increasing aggressiveness, recent congestion control algorithms (CCAs) can quickly starve standard TCP flows in their shared router queues. Existing solutions based on fair queueing are not scalable enough, and those based on admission control do not fit all CCAs. Independently, building on the popularization of machine learning, recent papers have designed several CCA classifiers.In this seminar, we introduce a buffer isolation mode where incoming flows first...

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Pixel Club: FreeAugment: Data Augmentation Search Across All Degrees of Freedom

Tom Bekor - The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering

Tuesday, 09.04.2024, 11:30

Room 1061, EE Meyer Building

Graduate Seminar
Data augmentation has become an integral part of deep learning, as it is known to improve the generalization capabilities of neural networks.Since the most effective set of image transformations differs between tasks and domains, automatic data augmentation search aims to alleviate the extreme burden of manually finding the optimal image transformations. However, current methods are not able to jointly optimize all degrees of freedom: (1)...

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PAT-CEP : Statistical Guarantee for ML-based Complex Event Processing

In the landscape of data stream processing, the challenges posed by online problems are of paramount importance. This paper introduces a pioneering method tailored to address these challenges within the context of data streams. While our initial focus centered on Complex Event Processing (CEP) problems, it is essential to underscore the versatility of our approach, as it is equally applicable to a diverse range of online problems. To the best of our knowledge, there exists no comp...

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TDC Seminar: Fault-Tolerant Labeling and Compact Routing Schemes

Michal Dory, Haifa University

Monday, 08.04.2024, 13:30

Zisapel (ECE) 608

Assume that you have a huge graph, where edges and vertices may fail, and you want to answer questions about this graph quickly, without inspecting the whole graph. A fault-tolerant labeling scheme allows us to do just that. It is a distributed data structure, in which each vertex and edge is assigned a short label, such that given the labels of a pair of vertices s,t, and a set of failures F, you can answer questions about s and t in G\F. For example, determine if s and t are con...

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DEPTH: Discourse Education through Pre-Training Heirarchically

Zachary Elisha Bamberger

Sunday, 07.04.2024, 10:00

Room 601

Language Models (LMs) excel in many tasks, but understanding discourse – how sentences connect to form coherent text – remains a challenge. This is especially true for smaller models aiming to match the abilities of their larger counterparts in handling long and complex inputs. To address this, we introduce DEPTH, a new encoder-decoder model designed to foster robust discourse-level representations during the pre-training phase. DEPTH uniquely combines hierarchical sentence re...

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Learning with visual foundation models for Gen AI

Gal Chechik, Bar-Ilan University and NVIDIA

Thursday, 04.04.2024, 10:30

Taub 337

Between training and inference, lies a growing class of AI problems that involve fast optimization of a pre-trained model for a specific inference task. These are not pure “feed-forward” inference problems applied to a pre-trained model, because they involve some non-trivial inference-time optimization beyond what the model was trained for; neither are they training problems, because they focus on a specific input. These compute-heavy inference workflows raise new challenges i...

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CS RESEARCH DAY 2024

Wednesday, 03.04.2024, 12:30

CS Taub Lobby

The 12th CS Research Day for graduate studies will be held on Wednesday, April 03, 2024 between 12:30-14:30, at the lobby of the CS Taub Building.
Research Day events are opportunity for our graduate students to expose their researches using posters and presentations to CS faculty and all degrees students, Technion distinguished representatives and to high-ranking delegates from the hi-tech leading industry companies in Israel and abroad.
The participating researches will be on...

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Theory Seminar: Toward Better Depth Lower Bounds: A KRW-like theorem for Strong Composition

Or Meir (Haifa University)

Wednesday, 03.04.2024, 12:15

Taub 201

One of the major open problems in complexity theory is proving super-logarithmic lower bounds on the depth of circuits. Karchmer, Raz, and Wigderson (Computational Complexity 5(3/4), 1995) suggested approaching this problem by proving that depth complexity of a composition of two functions is roughly the sum of their individual depth complexities. They showed that the validity of this conjecture would imply the desired lower bounds.The intuition that underlies the KRW conj...

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CE-Club:Here Comes the GenAI Malware, Worm, and APT

Ben Nassi, Technion

Wednesday, 03.04.2024, 11:30

Meyer 861

In the past year, numerous companies have incorporated Generative AI (GenAI) capabilities into new and existing applications, forming interconnected Generative AI (GenAI) ecosystems consisting of applications powered by GenAI services.While ongoing research highlighted risks associated with the GenAI layer of agents (e.g., dialog poisoning, membership inference, prompt leaking, jailbreaking), a critical question emerges: Can attackers develop malware to exploit the GenAI c...

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Marrying Vision and Language: A Mutually Beneficial Relationship?

Hadar Averbuch-Elor, Tel-Aviv University

Tuesday, 02.04.2024, 14:30

Taub 337

Foundation models that connect vision and language have recently shown great promise for a wide array of tasks such as text-to-image generation. Significant attention has been devoted towards utilizing the visual representations learned from these powerful vision and language models. In this talk, I will present an ongoing line of research that focuses on the other direction, aiming at understanding what knowledge language models acquire through exposure to images during pretraini...

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Pixel-Club: STMPL: Human Soft-Tissue Simulation

Anton Agafonov (Graduate Seminar)

Tuesday, 02.04.2024, 11:30

Room 608, Zisapel Building

In various applications, such as virtual reality and gaming, simulating the deformation of soft tissues in the human body during interactions with external objects is essential. Traditionally, Finite Element Methods (FEM) have been employed for this purpose, but they tend to be slow and resource-intensive. In this paper, we propose a unified representation of human body shape and soft tissue with a data-driven simulator of non-rigid deformations. This approach enables rapid simula...

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StarkWare - Engineering the Future of Blockchain

StarkWare

Monday, 01.04.2024, 12:30

The graduate students' lounge, room 225

Engineering the Future of Blockchain
1.4.23 | 12:30-14:30 | The graduate students' lounge, Taub, 2nd floor
12:30 - Mingling and Snacks
13:00 - Oded Naor, Ph.D., Product Manager - Btockchain reinvented: a deep dive into StarkWare's game-changing sotutions
13:30 - Noa Oved, MSC, Software Team Lead - Coding the future: Transforming algorithmic insights into real-wortd sotutions
14:00- Q&A
Plese RSVP at...

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Open day for March 28. Getting Started!

Thursday, 28.03.2024, 09:30

Technion

An open day for studies at the Technion will be held on Thursday, March 28, starting at 09:30
For details and registration, go to the registration and admission website at the link
...

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Theory Seminar: Exploring the Generalization Ability of (Convex) Optimization Algorithms

Tomer Koren (Tel-Aviv University)

Wednesday, 27.03.2024, 12:15

Taub 201

In machine learning, there has been considerable interest over the past decade in understanding the ability of optimization algorithms to generalize—namely, to produce solutions (models) that extend well to unseen data—particularly in the context of overparameterized problems. I will survey several recent theoretical studies that explore generalization in classical convex optimization, that reveal intriguing behavior of common optimization methods and shed some light on the c...

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Guest seminar - How to design innovative software?

Prof. Daniel Jackson, MIT

Wednesday, 27.03.2024, 12:00

Auditorium 012, floor 0

I will explain how successful innovations in software can usually be traced to just one or two "concepts" that offer new scenarios that, with seemingly small shifts, radically change how an application is used. I give examples from apps such as Zoom, WhatsApp and Calendly. I explain how concepts, each with their own characteristic scenarios, can be composed to form apps. I explain how this idea can be used to make software more usable, modular and consistent.
More information at:...

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CE-Club: Optimizing Information Freshness in Wireless Networks: From Theory to Implementation

Eytan Modiano - Laboratory for Information and Decision Systems Massachusetts Institute of Technology

Wednesday, 27.03.2024, 11:30

Meyer 861

Age of Information (AoI) is a recently proposed performance metric that captures the freshness of the information from the perspective of the application. AoI measures the time that elapsed from the moment that the most recently received packet was generated to the present time. In this talk, we explore the AoI optimization problem in wireless networks.We start by considering a wireless network with a number of nodes transmitting information to a base station and develop l...

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Intel's tech experience is coming to campus!

Wednesday, 27.03.2024, 10:00

EE Meyer Building

Intel's tech experience is coming to campus!
Ready for the most innovative technological picnic you've ever seen?
We have loaded technological tools and our greatest minds to the track and we are on our way to you
Wednesday 27.3 | Mayer building, 3rd floor
10:00 - AR | VR | HR Come and get to know us and our technologies
12:30 - FPGA MicroPython
The number of places is limited, register at the ...

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Pixel-Club: Idempotent Generative Network

Assaf Shocher, NVIDIA

Tuesday, 26.03.2024, 11:30

Room 1061, EE Meyer Building

We propose a new approach for generative modeling based on training a neural network to be idempotent. An idempotent operator is one that can be applied sequentially without changing the result beyond the initial application, namely f(f(z))=f(z). The proposed model f is trained to map a source distribution (e.g, Gaussian noise) to a target distribution (e.g. realistic images) using the following objectives: (1) Instances from the target distribution should map to themselves, namel...

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The Altru-Egoistic Approach to Collaborative Caching

In this lecture we will explore collaborative caching algorithms in order to boost the effectiveness of caches in a distributed storage system. I'll introduce a scheme that partitions each node’s cache into two conceptual regions: an egoistic area whose goal is to contain the most valuable data for the node that owns the cache, and an altruistic area whose goal is to contain the most valuable data for the system as a whole. Each node’s division between these two regions is dyn...

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Pixel-Club: Explaining Classification by Image Decomposition

Elnatan Kadar (Graduate Seminar)

Wednesday, 20.03.2024, 14:30

Room 1061, EE Meyer Building

We propose a new way to explain and to visualize neural network classification through a decomposition-based explainable AI.
Instead of providing an explanation heatmap, our method yields a decomposition of the image into class-agnostic and class-distinct parts, with respect to the data and chosen classifier. Following a fundamental signal processing paradigm of analysis and synthesis, the original image is the sum of the decomposed parts. We thus obtain a radically different way ...

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Theory Seminar: Deterministic Online embedding of metrics

Ilan Newman (University of Haifa)

Wednesday, 20.03.2024, 13:15

Taub 201

A finite metric space $(X,d)$ on a set of points $X$ is just the shortest path metric $d$ on a positively weighted graph $G=(X,E)$. In the online setting, the vertices of the input finite metric space $(X,d)$ are exposed one by one, together with their distances $d(*,*)$to the previously exposed vertices. The goal is to embed (map) $X$ into a given host metric space $(H,d_H)$ (finite or not) and so to distort the distances as little as possible (distortion is the worst cas...

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Mobileye Spotlight Day

Wednesday, 20.03.2024, 12:30

Taub Building

You are invited to the spotlight day of the Mobileye company at the Technion
Wednesday 20.3 | 12:30 | Taub Building...

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ceClub: From Dashboards To Labels: Helping Users Manage And Make Decision About Privacy

(George Washington University) Adam J Aviv

Wednesday, 20.03.2024, 11:30

Meyer 861 & Zoom Lecture:94673013539

The surveillance economy, where tracking and collecting data on uses for the purpose of advertising and other actions, is central to much of the money-making enterprises of the modern technology ecosystem. Due to regulations and other forces, some of the largest companies, such as Google and Apple, have prioritized mechanisms for users to better manage and receive information about the kinds of data that is being collected about them. In this talk, I will explore how effective the...

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Yahoo Is Coming To The Faculty On March 19 - Summer Internships And Research Opportunities

Tuesday, 19.03.2024, 12:30

CS Grads Club, Room 225

Yahoo holds a dedicated meeting with graduate students
Tuesday, March 19 at 12:30 p.m. at the CS Grads Club
In the program: an introduction to Yahoo's research in Israel and the summer internship program.
Register to the event here
waiting for you!!...

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Nvidia - Lecture And Pizza

Yarden Zuckerman, SW Security Manager, Nvidia

Monday, 18.03.2024, 18:00

Auditorium 012, floor 0

Join us for a lecture and pizza!
Cyber Security Challenges In The Modern Era
by Yarden Zuckerman, SW Security Manager, Nvidia
Monday | March 18, 2024 | 18:00 p.m. | Piano Auditorium Taub Building
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TDC Seminar: Null Messages, Information and Coordination

Raissa Nataf

Monday, 18.03.2024, 13:30

Zisapel (ECE) 608

I'll present our paper about the role that null messages play in synchronous systems with and without failures. Our work provides necessary and sufficient conditions on the structure of protocols for information transfer and coordination there. We start by introducing a new and more refined definition of null messages. A generalization of message chains that allow these null messages is provided and is shown to be necessary and sufficient for information transfer in reliable syste...

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Theory Seminar: A Unified Characterization Of Private Learning

Hilla Schefler (Technion)

Wednesday, 13.03.2024, 12:15

Taub 201

Differential Privacy (DP) is a mathematical framewirk for ensuring the privacy of individuals in a dataset. Roughly speaking, it guarantees that privacy is protected in data analysis by ensuring that the output of an analysis does not reveal sensitive information about any specific individual, regardless of whether their data is included in the dataset or not.This talk presents a unified framework for characterizing both pure and approximate differentially private learnabi...

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Window-Based Distribution Shift Detection for Deep Neural Networks

To deploy and operate deep neural models in production, the quality of their predictions, which might be contaminated benignly or manipulated maliciously by input distributional deviations, must be monitored and assessed. Specifically, we study the case of monitoring the healthy operation of a deep neural network (DNN) receiving a stream of data, with the aim of detecting input distributional deviations over which the quality of the network’s predictions is potentially damaged. ...

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Active Propulsion Noise Shaping For Multi-Rotor Aircraft Localization

Multi-rotor aerial autonomous vehicles (MAVs) primarily rely on vision for navigation purposes. However, visual localization and odometry techniques suffer from poor performance in low or direct sunlight, a limited field of view, and vulnerability to occlusions. Acoustic sensing can serve as a complementary or even alternative modality for vision in many situations, and it also has the added benefits of lower system cost and energy footprint, which is especially important for micr...

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Pixel-Club: Using Zodiacal Light For Spaceborne Calibration Of Polarimetric Imagers

Or Avitan (Graduate Seminar)

Tuesday, 12.03.2024, 11:30

Room 1061, EE Meyer Building

We propose that spaceborne polarimetric imagers can be calibrated, or self-calibrated using zodiacal light (ZL). ZL is created by a cloud of interplanetary dust particles. It has a significant degree of polarization in a wide field of view. From space, ZL is unaffected by terrestrial disturbances. ZL is insensitive to the camera location, so it is suited for simultaneous cross-calibration of satellite constellations. ZL changes on a scale of months, thus being a quasi-constant tar...

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TDC Seminar: From Distributed Computing to Cryptography and Back

Ittai Abraham, Intel

Monday, 11.03.2024, 13:30

Zisapel (ECE) 608

I will share some of my learnings from working on problems on the intersection of Distributed Computing and Cryptography.On the one hand, I will show how some cryptographic protocols (MPC and DKG) can be improved by using distributed computing counterparts for notions such as zero knowledge proofs and proofs of knowledge. On the other hand, I will show how distributed computing protocols (ABA) can be improved by carefully using notions of binding from cryptography. One rec...

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On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-based Method

Most works on modeling the conversation history in Conversational Question Answering (CQA) report a single main result on a common CQA benchmark. While existing models show impressive results on CQA leaderboards, it remains unclear whether they are robust to shifts in setting (sometimes to more realistic ones), training data size (e.g. from large to small sets) and domain. In this work, we design and conduct the first large-scale robustness study of history modeling approaches for...

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Nvidia Invites You To a Virtual Spotlight Day 10/3

Sunday, 10.03.2024, 18:00

Meet virtually

Nvidia invites you to a virtual spotlight day where the company's engineers will talk about the different groups and open positions
Sunday, March 10, from 18:00 to 19:30
To register for the event here...

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Cadence Arrive For Recruitment Day At The Faculty

Wednesday, 06.03.2024, 12:30

CS Taub Lobby

Cadence company is coming to a spotlight day at the faculty
Wednesday 6/3 | 12:30-14:30 | Lobby Taub
In the program: a meeting with the recruitment teams, the engineers for a 1:1 conversation about employment opportunities and tips for writing a report.
And of course merch and sweets.
waiting for you!!...

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Faster Matrix Game Solvers Via Ball Oracle Acceleration

Yair Carmon (Tel-Aviv university)

Wednesday, 06.03.2024, 12:15

Taub 201

We design a new stochastic first-order algorithm for approximately solving matrix games as well as the more general problem of minimizing the maximum of smooth convex functions. Our central tool is ball oracle acceleration: a technique for minimizing any convex function with a small number of calls to a ball oracle that minimizes the same function restricted to a small ball around the query point. To design an efficient ball oracle for our problems of interest we leverage stochast...

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Early Time Classification with Accumulated Accuracy Gap Control

Early time classification algorithms aim to label a stream of features without processing the full input stream, while maintaining accuracy comparable to that achieved by applying the classifier to the entire input. In this paper, we introduce a statistical framework that can be applied to any sequential classifier, formulating a calibrated stopping rule. This data-driven rule attains finite-sample, distribution-free control of the accuracy gap between full and early-time classifi...

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Mor Filo, a graduate of the faculty and a developer at Amazon

Monday, 04.03.2024, 18:30

Auditorium 012, floor 0

You have been accepted as a student! What now?
The student community at the SHE S faculty invites you to a meeting on:
First time student job: about the opportunities, challenges and skills you acquire in your first job
Monday, 4/3 at 6:30 pm in the piano auditorium
Please register in advance: here
Speaker: Moore Philo, graduate of the faculty and developer at Amazon
The meeting is suitable for thos...

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Stable Tuple Embeddings for Dynamic Databases

We study the problem of computing an embedding of the tuples of a relational database
in a manner that is extensible to dynamic changes of the database. In this problem,
the embedding should be stable in the sense that it should not change on the existing
tuples due to the embedding of newly inserted tuples (as database applications might
already rely on existing embeddings); at the same time, the embedding of all tuples, old
and new, should retain high quality. This task is chall...

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Spotlight Day For Nvidia At The Technion

Wednesday, 28.02.2024, 12:30

CS Taub Lobby

Spotlight day for Nvidia at the Technion on February 28, 2024
Nvidia is coming to meet the students of the Faculty of Computer Science at the Technion!
Come and meet the company's engineers face to face
Wednesday February 28, 2024 | 12:30-14:30 | Taub lobby, floor 0...

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Distance Sensitivity Oracles

Sarel Cohen (Tel-Aviv Academic College)

Wednesday, 28.02.2024, 12:15

Taub 201

Theory Seminar: An f-edge fault-tolerant distance sensitivity oracle (f-DSO) is a data-structure that, when queried with two vertices (s, t) and a set F of at most f edges of a graph G with n vertices, returns an estimate tilde{d}(s,t,F) of the distance d(s,t,F) from s to t in G – F. The oracle has stretch alpha if the estimate satisfies d(s,t,F) le tilde{d}(s,t,F) le alpha cdot d(s,t,F) . In the last two decades, extensive research has focused on developing efficient f-DSOs. Th...

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TDC Seminar: Fast and Fair Lock-Free Locks

Naama Ben-David, Technion

Monday, 26.02.2024, 13:30

Zisapel (ECE) 608

Locks are frequently used in concurrent systems to simplify code and ensure safe access to contended parts of memory. However, they are also known to cause bottlenecks in concurrent code, leading practitioners and theoreticians to sometimes opt for more intricate lock-free implementations. In this talk, I’ll show that, despite the seeming contradiction, it is possible to design practically and theoretically efficient lock-free locks; I'll present a lock-free lock algorithm with ...

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Fundamental Problems in AI: Transferability, Compressibility and Generalization

In this talk, we delve into several fundamental questions in deep learning. We start by addressing the question, "What are good representations of data?" Recent studies have shown that the representations learned by a single classifier over multiple classes can be easily adapted to new classes with very few samples. We offer a compelling explanation for this behavior by drawing a relationship between transferability and an emergent property known as neural collapse. Later, we expl...

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Theory and Practice of DNA Storage

In the last decade, DNA-based storage systems emerged as a potential data archival solution due to their high data density and durability. This research delves into intrinsic error characteristics of DNA storage systems to devise robust coding strategies and innovative algorithms for enhanced reliability, efficiency, scalability, and cost-effectiveness. The research propels DNA storage feasibility while contributing to foundational theory.The work analyzes combinatorial st...

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Identifying Underlying Geometry To Analyze High-Dimensional Data: Images And Shape Spaces As A Case Study

High-dimensional data is increasingly available in diverse applications, ranging from images to shapes represented as point clouds. Such data raises novel questions and offers a unique opportunity to study them by developing new machine-learning tools. While the analysis of an individual sample may be challenging, leveraging the power of the data collection can be effective in tackling complex tasks. This talk delves into the challenges associated with studying such data, particul...

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Theory Seminar: IOPs with Inverse Polynomial Soundness Error

Gal Arnon (Weizmann institute)

Wednesday, 21.02.2024, 12:15

Taub 201

We show that every language in NP has an Interactive Oracle Proof (IOP) with inverse polynomial soundness error and small query complexity. This achieves parameters that surpass all previously known PCPs and IOPs. Specifically, we construct an IOP with perfect completeness, soundness error 1/n, round complexity O(loglog n), proof length poly(n) over an alphabet of size O(n), and query complexity O(loglog n). This is a step forward in the quest to establish the sliding-scale conjec...

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TDC Seminar: Deterministic Distributed Maximum Weight Independent Set Approximation in Sparse Graphs

Yuval Gil, Technion

Monday, 19.02.2024, 13:30

Zisapel (ECE) 608

This talk focuses on the distributed task of constructing an approximate \emph{maximum weight independent set (MWIS)}.
Specifically, we are interested in deterministic CONGEST algorithms whose approximation guarantees are expressed as a function of the graph's \emph{arboricity} $\alpha$.Generally speaking, efficient deterministic non-trivial approximation algorithms for MWIS were not known until the recent breakthrough of Faour et al.~[SODA 2023] that obtained an $O(\Delta...

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A Deep Learning Platform for Diagnosing ECG Tests

In clinical settings, a significant portion of ECG data is typically available in printed form, and the most convenient means of digitizing this information involves utilizing a mobile device. Despite notable progress in AI-based techniques for paper-based 12-lead ECG analysis, their adoption in clinical practice remains limited primarily due to challenges such as inadequate accuracy in clinical settings and a restricted ability to diagnose various cardiac conditions.
Our objectiv...

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Theory Seminar: Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension

Idan Mehalel (Technion)

Wednesday, 14.02.2024, 12:15

Taub 201

Suppose that n forecasting experts (or functions) are providing daily rain/no-rain predictions, and the best among them is mistaken in at most k many days. For how many days will a person allowed to observe the predictions, but has no weather-forecasting prior knowledge, mispredict?In this talk, we will discuss how such classical problems can be reduced to calculating the (average) depth of binary trees, by using newly introduced complexity measures (aka dimensions) of the...

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ceClub: Space-efficient FTL for Mobile Storage via Tiny Neural Nets

Ron Marcus

Wednesday, 14.02.2024, 11:30

Meyer 861

With the rapid increase of storage demands and working sets of modern mobile apps, maintaining high I/O performance in mobile SSDs under strict resource constraints is challenging. The Flash Translation Layer (FTL) must increase the capacity of the Logical-To-Physical (L2P) address translation cache to keep up with the new workloads, but it comes at the cost of scaling the on-die SRAM, resulting in higher chip area, power consumption, and costs.In this talk, I will present...

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Technion CTF Team

Tuesday, 13.02.2024, 18:30

Taub 2

Come be part of a new Capture The Flag-CTF group at the Faculty
The meetings are held every Tuesday at 18:30 at Taub 9 and include guest lectures and practical experience in solving challenges.
Everybody is invited! Beginners and experienced
For details: Technionctf.com
This week - February 13, 2024:
18:30 | Taub 2 | Omar Atias - security researcher, lecturer at BlackHat USA & DEFCON
The price of con...

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A 0-RTT-Aware QUIC Load Balancer

QUIC is an emerging transport protocol, offering multiple advantages over TCP. Yet, to fully unleash QUIC’s potential, a paradigm shift is needed in existing network infrastructure. We propose a novel 0-RTT-aware load balancing algorithm. 0-RTT is crucial for web performance, particularly on mobile networks. Our load balancing algorithm ensures 0-RTT while maintaining near-optimal load balancing performance.Through extensive simulations, using both synthetic and real-wor...

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Final Spotlight Day

Wednesday, 07.02.2024, 12:30

Auditorium 012, floor 0

You are invited to Final spotlight day
Wednesday 07.02.2024 | 12:30-14:30 | Visitor Center Auditorium 012, Floor 0
12:30 - Come meet engineers, researchers and the recruitment team at Final, and get to know the day-to-day life at Final.
13:15 - Meeting on options, probabilities and the world of algorithm trading | Noam Horowitz - researcher at Final
To register for the lecture click ...

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Theory Seminar: Algorithmic Cheap Talk

Konstantin Zabaranyi (Technion)

Wednesday, 07.02.2024, 12:15

Taub 201

Come be part of a new Capture The Flag-CTF group at the Faculty
The meetings are held every Tuesday at 18:30 at Taub 9 and include guest lectures and practical experience in solving challenges.
Everybody is invited! Beginners and experienced
For details: Technionctf.com
The week of February 6, 2024:
Beginners: Forensics & Networks | Taub 9
experienced: Challenges from 2023 LA CTF | Tau...

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Technion CTF Team

Tuesday, 06.02.2024, 18:30

Taub 9

Come be part of a new Capture The Flag-CTF group at the Faculty
The meetings are held every Tuesday at 18:30 at Taub 9 and include guest lectures and practical experience in solving challenges.
Everybody is invited! Beginners and experienced
For details: Technionctf.com
The week of February 6, 2024:
Beginners: Forensics & Networks | Taub 9
experienced: Challenges from 2023 LA CTF | Taub 8...

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Constrictor: Immutability as a Design Concept

Elad Kinsbruner

Tuesday, 06.02.2024, 12:30

Taub 601

Many object-oriented applications in algorithm design rely on objects never changing during their lifetime. This is often tackled by marking object references as read-only, e.g., using the const keyword in C++. In other languages like Python or Java where such a concept does not exist, programmers rely on best practices that are entirely unenforced. While reliance on best practices is obviously too permissive, const-checking is too restrictive: it is possible for a method to mutat...

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Pixel-Club: Robustified ANNs Reveal Wormholes Between Human Category Percepts

Guy Gaziv (DiCarlo Lab at MIT)

Tuesday, 06.02.2024, 11:30

Room 1061, EE Meyer Building

The visual object category reports of artificial neural networks (ANNs) are notoriously sensitive to tiny, adversarial image perturbations. Because human category reports (aka human percepts) are thought to be insensitive to those same small-norm perturbations — and locally stable in general — this argues that ANNs are incomplete scientific models of human visual perception. Consistent with this, we show that when small-norm image perturbations are generated by standard ANN mo...

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Theory Of Crypto Seminar: Perfect Asynchronous MPC with Linear Communication Overhead

Gilad Asharov (Bar Ilan University)

Thursday, 01.02.2024, 11:30

Taub 401

We study secure multiparty computation in the asynchronous setting with perfect security and optimal resilience (less than one-fourth of the participants are malicious). It has been shown that every function can be computed in this model [Ben-OR, Canetti, and Goldreich, STOC'1993].
Despite 30 years of research, all protocols in the asynchronous setting require $\Omega(n^2C)$ communication complexity for computing a circuit with $C$ multiplication gates. In contrast, for nearly 15...

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Almost Logarithmic Approximation for Cutwidth and Pathwidth

Dor Katzelnick

Wednesday, 31.01.2024, 12:30

Taub 201

We study several graph layout problems with a min max objective. Here, given a graph we wish to find a linear ordering of the vertices that minimizes some worst case objective over the natural cuts in the ordering; which separate an initial segment of the vertices from the rest. A prototypical problem here is cutwidth, where we want to minimize the maximum number of edges crossing a cut. The only known algorithm here is by [Leighton-Rao J.ACM 99] based on recursively partitioning ...

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Theory Seminar: Almost Logarithmic Approximation for Cutwidth and Pathwidth

Dor Katzelnick (Technion)

Wednesday, 31.01.2024, 12:15

Taub 201

We study several graph layout problems with a min max objective. Here, given a graph we wish to find a linear ordering of the vertices that minimizes some worst case objective over the natural cuts in the ordering; which separate an initial segment of the vertices from the rest. A prototypical problem here is cutwidth, where we want to minimize the maximum number of edges crossing a cut. The only known algorithm here is by [Leighton-Rao J.ACM 99] based on recursively partitioning ...

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ceClub: Challenges and Opportunities In Securing Software Supply Chains

Dr. Yaniv David (Columbia University)

Wednesday, 31.01.2024, 11:30

Meyer 861

Racing to be first to market and deploy new features, developers rely on many external libraries to underpin their software. Each library uses more libraries, creating vast networks of dependencies that the developers know little about and have no control over, forming a knowledge gap that quickly turns into technical debt. Repaying this debt is difficult, as analyzing or examining all libraries is infeasible, and worse, the debt keeps growing due to frequent library updates. Atta...

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CS Lecture: On Implicit Bias and Benign Overfitting in Neural Networks

Gal Vardi

Wednesday, 31.01.2024, 10:30

Taub 601

When training large neural networks, there are typically many solutions that perfectly fit the training data. Nevertheless, gradient-based methods often have a tendency to reach those which generalize well, namely, perform well also on test data. Thus, the training algorithm seems to be implicitly biased towards certain networks, which exhibit good generalization performance. Understanding this “implicit bias” has been a subject of extensive research recently. Moreover, in con...

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Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines

Michael Toker

Monday, 29.01.2024, 15:30

Taub 601

Text-to-image diffusion models (T2I) use a latent representation of a text prompt to guide the image generation process.
However, the encoder that produces the text representation is largely unexplored. We propose the Diffusion Lens, a method for analyzing the text encoder of T2I models by generating images from its intermediate representations. Using the Diffusion Lens, we perform an extensive analysis of two recent T2I models.We find that the text encoder gradually build...

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CS Lecture: Verification of Complex Hyperproperties

Hadar Frenkel

Sunday, 28.01.2024, 10:30

Auditorium 012, floor 0

Hyperproperties are system properties that relate multiple execution traces to one another. Hyperproperties are essential to express a wide range of system requirements such as information flow and security policies; epistemic properties like knowledge in multi-agent systems; fairness; and robustness. With the aim of verifying program correctness, the two major challenges are (1) providing a specification language that can precisely express the desired properties; and (2) providin...

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Theory Seminar: The Sample Complexity Of ERMs In Stochastic Convex Optimization

Daniel Carmon (Technion)

Wednesday, 24.01.2024, 12:15

Taub 201

Stochastic convex optimization is one of the most well-studied models for learning in modern machine learning. Nevertheless, a central fundamental question in this setup remained unresolved:
How many data points must be observed so that any empirical risk minimizer (ERM) shows good performance on the true population?
This question was proposed by Feldman who proved that Ω(\frac{d}{ϵ} + \frac{1}{ϵ^2}) data points are necessary (where d is the dimension and ε > 0 is the accurac...

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The Technion CTF Team opens at the Faculty

Tuesday, 23.01.2024, 18:30

Taub 9

The Technion CTF Team opens at the Faculty
We invite you to join the Capture The Flag - CTF meetings. CTF is a cyber challenge competition and information security on the topics: cryptography, reverse engineering, forensics, web, etc. The meetings will include guest lectures and practical experience in solving challenges.
Beginner and experienced students are welcome to join.
The first introductory meeting will be held on Tuesday, January 23 at 6:30 pm at Taub 9.
In the f...

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CGGC Seminar: Poisson Manifold Reconstruction (beyond co-dimension one)

Prof. Misha Kazhdan (Computer Science, Johns Hopkins University)

Thursday, 18.01.2024, 11:30

Taub 012 (Learning Center Auditorium)

In this talk we consider the problem of manifold reconstruction from oriented point clouds for embedded manifolds of co-dimension larger than one. Using the framework of Poisson Surface Reconstruction, and formulating the problem in the language of alternating products, we show that the earlier approach for reconstructing hyper-surfaces extends to general manifolds, at the cost of replacing a quadratic energy with a multi-quadratic energy. We provide an efficient iterative hierarc...

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Theory Seminar: Online edge coloring

David Wajc (Technion)

Wednesday, 17.01.2024, 12:15

Taub 201

Vizing’s Theorem provides an algorithm that edge colors any graph of maximum degree Δ using Δ+1 colors, which is necessary for some graphs, and at most one higher than necessary for any graph. In online settings, the trivial greedy algorithm requires 2Δ-1 colors, and Bar-Noy, Motwani and Naor in the early 90s showed that this is best possible, at least in the low-degree regime. In contrast, they conjectured that for graphs of superlogarithmic-in-n maximum degree, much better ...

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Internet-Scale Consensus in the Blockchain Era

Joachim Neu

Tuesday, 16.01.2024, 11:00

Taub 601

Blockchains have ignited interest in Internet-scale consensus as a vital building block for decentralized applications and services that promise egalitarian access and robustness to faults and abuse. While the study of consensus has a 40+ year tradition, the new Internet-scale setting requires a fundamental rethinking of models, desiderata, and protocols. An emergent key challenge is to simultaneously serve clients with different requirements regarding the two fundamental aspects ...

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12-Lead ECG Classification Using Deep Learning Methods

Vadim Gliner

Thursday, 04.01.2024, 12:30

Faculty of Biomedical Engineering, Silver Building, Room 201

12-lead electrocardiogram (ECG) recordings can be collected in any clinic and the interpretation is performed by a clinician. Modern machine learning tools may make them automatable. However, a large fraction of 12-lead ECG data is still available in printed paper or image only and comes in various formats. To digitize the data, smartphone cameras can be used. Nevertheless, this approach may introduce various artifacts and occlusions into the obtained images.Here, I will p...

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CS Lecture: Learning From Dependent Data And Its Modeling Through The Ising Model

Yuval Dagan

Monday, 01.01.2024, 10:30

Auditorium 012, floor 0

I will present a theoretical framework for analyzing learning algorithms which rely on dependent, rather than independent, observations. While a common assumption is that the learning algorithm receives independent datapoints, such as unrelated images or texts, this assumption often does not hold. An example is data on opinions across a social network, where opinions of related people are often correlated, for example as a consequence of their interactions. I will present a line o...

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