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The Taub Faculty of Computer Science Events and Talks

TCE-MLIS 2021 Conference
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Thursday, 24.2.2022, 08:30
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ELMA Arts Complex, Zichron Ya'acov
MLIS, the Technion AI center, in collaboration with TCE, would like to invite you to participate in the annual MILS-TCE conference. AI is now a major buzz word everywhere and expectations are sky-rocketing, but what is true state-of-the-art and what can be actually implemented in the AI and Machine Learning fields? In a series of lectures, Technion researchers will present cutting-edge AI research conducted in the institution. Simultaneously, in thematic workshops we will explore the ...
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ILP Based Load Balancing in Deduplicated Storage Systems
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Ariel Kolikant
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Sunday, 6.2.2022, 12:00
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Zoom Lecture: 97413372304
Deduplication reduces the size of the data stored in large-scale storage systems by replacing duplicate data blocks with references to their unique copies. This creates dependencies between files that contain similar content and complicates the management of data in the system. In the work presented in this seminar, we have addressed the problem of data migration, where files are remapped between different volumes because of system expansion or maintenance. The challenge of determining which files ...
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Clustering Based Data Migration in Deduplicated Storage
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Roei Kisous
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Tuesday, 1.2.2022, 13:30
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Zoom Lecture: 8183278482
Deduplication is a leading method for reducing physical storage capacity when duplicate data is present. This method can be applied on chunks, files, containers, and more. Instead of storing the same physical data multiple times, a pointer is created from each logical copy to the same physical copy, saving the space of the duplicate data. Due to this, data is shared between objects, such as files or entire directories, which result in garbage collection overhead ...
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CGGC Seminar: Trading Memory for Computations: Scaling Range Matching on the Critical Path
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Alon Rashelbach (EE, Technion)
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Sunday, 30.1.2022, 13:30
Range matching (RM) is a crucial component in computer systems, widely used in address translation, hard drives, network switches, and many more applications. RM is performed whenever one wishes to locate a range that contains an input number, given a large set of ranges. Any page-based mechanism uses RM, as pages are basically ranges. Longest prefix matching (LPM) uses ternary rules, which are also ranges. Firewalls are one example of multidimensional RM since ACL rules ...
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pISTA: preconditioned Iterative Soft Thresholding Algorithm for Graphical Lasso
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Gal Shalom
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Wednesday, 26.1.2022, 10:30
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Zoom Lecture: 91228689582
We propose a novel quasi-Newton method for solving the sparse inverse covariance estimation problem also known as the graphical least absolute shrinkage and selection operator (GLASSO). This problem is often solved using a second order quadratic approximation. However, in such algorithms the Hessian term is complex and computationally expensive to handle. To this end,our algorithm uses the inverse of the Hessian as a preconditioner to simplify and approximate the quadratic element at the cost of ...
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Pixel Club: TextAdaIN: Paying Attention to Shortcut Learning in TextRecognizers
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Oren Nuriel (AWS)
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Tuesday, 25.1.2022, 11:30
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Zoom Lecture: https://technion.zoom.us/my/chaimbaskin
Leveragingthe characteristics of convolutional layers, neural networks are extremelyeffective for pattern recognition tasks. However in some cases,their decisions are based on unintended information leading to high performanceon standard benchmarks but also to a lack of generalization to challengingtesting conditions and unintuitive failures. Recentworkhas termed this “shortcut learning” and addressed its presence in multipledomains. In text recognition, we reveal another such shortcut, whereby recognizersoverly depend on local image statistics. Motivated by this, we suggest anapproach to ...
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Solving Constrained Horn Clauses Lazily and Incrementally
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Omer Rappoport
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Tuesday, 25.1.2022, 10:30
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Zoom Lecture: 93910185113
Constrained Horn Clauses (CHCs) is a fragment of First Order Logic (FOL), that has gained a lot of attention in recent years. One of the main reasons for the rising interest in CHCs is the ability to reduce many verification problems to satisfiability of CHCs. For example, program verification can naturally be described as the satisfiability of CHCs modulo a background theory such as linear arithmetic and arrays. To this end, CHC-solvers can be used ...
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Efficient Self-Supervised Data Collection for Offline Robot Learning
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Shadi Endrawis
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Monday, 24.1.2022, 15:00
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Zoom Lecture: 7446114621
a large batch of real or simulated robot interaction data, using some data collection policy, and then learn from this data to perform various tasks, using offline learning algorithms. Previous work focused on manually designing the data collection policy, and on tasks where suitable policies can easily be designed, such as random picking policies for collecting data about object grasping. For more complex tasks, however, it may be difficult to find a data collection policy ...
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CS LECTURE: Mathematical Foundations of Robust Geometry and Fabrication
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Oded Stein (MIT)
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Monday, 24.1.2022, 15:00
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Zoom Lecture: 91550335554
Current geometry methods for creating and manipulating shapes on computers can sometimes be unreliable and fail unpredictably. Such failures make geometry tools hard to use, prevent non-experts from creating geometry on their computers, and limit the use of geometry methods in domains where reliability is critical. We will discuss my recent efforts in proving when existing methods work as intended, my work in making methods more robust to imperfect input, my work in the creation ...
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SMEGA2: Distributed Deep Learning Using a Single Momentum Buffer
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Refael Cohen
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Monday, 24.1.2022, 10:00
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Zoom Lecture: 92984244781
As the field of deep learning progresses, and models become larger and larger, training deep neural networks has become a demanding task. The task requires a huge amount of compute power, and can still be very time consuming - especially when using just a single GPU. To tackle this problem, distributed deep learning has come into play, with various asynchronous training algorithms. However, most of these algorithms suffer from decreased accuracy as the number of ...
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Mathematical Techniques for Cryptanalysis
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Stav Perle
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Thursday, 20.1.2022, 15:00
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Zoom Lecture: 92017151302
Symmetric ciphers are cryptographic algorithms that use the same cryptographic keys for both encryption and decryption. The key represents a shared secret between users, that is used to maintain a private information link. In our research we focus on cryptanalysis of block ciphers, which are the most widely used realization of symmetric ciphers. Block ciphers are cryptosystems that consist of two algorithms, an encryption algorithm that accepts a symmetric key and a plaintext and outputs ...
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How to Avoid Depth Reconstruction in 3D Vision Tasks: Do We Need Depth in State-Of-The-Art Face Authentication?
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Amir Livne
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Tuesday, 18.1.2022, 13:30
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Zoom Lecture: 94951674375
Face recognition systems are frequently used in a variety of security applications in our daily lives. Some methods are designed to utilize geometric information extracted from depth sensors to overcome single-image-based recognition technologies’ weaknesses, such as vulnerability to illumination variations, large head poses, and spoofing attacks. However, the accurate acquisition of the depth profile or surface is an expensive and challenging process. We introduce a novel method to recognize faces from stereo camera systems without ...
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Pixel Club: Endless Loops: Detecting and Animating Periodic Patterns in Still Images
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Tavi Halperin (The Hebrew University of Jerusalem)
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Tuesday, 18.1.2022, 11:30
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Zoom Lecture: https://technion.zoom.us/my/chaimbaskin
We present an algorithm for producing a seamless animated loop from a single image. The algorithm detects periodic structures, such as the windows of a building or the steps of a staircase, and generates a non-trivial displacement vector field that maps each segment of the structure onto a neighboring segment along a user- or auto-selected main direction of motion. This displacement field is used, together with suitable temporal and spatial smoothing, to warp the image ...
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Bribery attack on Nakamoto Consensus Proof of Stake Protocols
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Tom Brand
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Sunday, 16.1.2022, 15:00
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Zoom Lecture: 7228552597
Bitcoin was introduced to the world in 2009 with Proof of Work (PoW) Leader Election as one of its novel building blocks. Since then, much criticism has been made of its high energy consumption. Proof of Stake protocols aims at replacing PoW protocols as a much more efficient version while still maintaining its security properties under the Honest Majority model. In our work, we show a bribery attack under the Rational Majority model, which breaks ...
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Securing ICS Protocols
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Alon Dankner
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Sunday, 16.1.2022, 10:30
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Zoom Lecture: 8899993884
Industrial Control Systems (ICSs), also known as Operation Technology (OT) systems, are distributed computerized systems designed to manage, monitor and control industrial processes. They are widely used in critical infrastructures, such as power plants and water supply, whose continuous operation is of major importance to modern life. Following the well-known Stuxnet attack on OT systems, a large investment in OT security was started. Though their cyber protection is crucial, they did not yet reach the ...
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CS LECTURE: Computing Using Time
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George Tzimpragos (UC Santa Barbara and Lawrence Berkeley National Laboratory)
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Wednesday, 12.1.2022, 17:30
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Zoom Lecture: 96743325005
The development of computing systems able to address our ever-increasing needs, especially as we reach the end of CMOS transistor scaling, requires truly novel methods of computing. My research draws inspiration from biology, rethinks the digital/analog boundary, and challenges conventional wisdom, which typically guides how we perform computation, by reimagining the role of time. In this talk, I first introduce a computational temporal logic that sets the foundation for temporal computing. Second, I demonstrate how ...
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An Automata Theory Method for the Analysis of Unicycle Pursuit Problems
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David Dovrat
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Wednesday, 12.1.2022, 13:30
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Zoom Lecture: 8206122066
The Pursuit Problem depicts a scenario where a moving target is pursued by an agent, whose movement is prescribed by some defined policy. Examples of what can be regarded as solutions to the pursuit problem include the shape of the agent's trajectory, whether the agent ultimately captures the target, and the circumstances of the capture, including the time required for capture to be achieved, The Unicycle Model is a popular simplification used to describe the ...
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Distributed Deep Neural Networks
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Ido Hakimi
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Tuesday, 11.1.2022, 13:00
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Zoom Lecture: 99195189391
Training deep neural networks in the distributed asynchronous setting is complicated. In the distributed asynchronous setting, the computational devices run in parallel, causing a delay in the propagation of information between the different computational devices. The delay is often referred to as staleness, which harms the training process and the quality of the deep neural network. This staleness is one of the main difficulties in scaling asynchronous settings to a large number of computational devices ...
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Pixel Club: Layered Neural Atlases for Consistent Video Editing
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Dolev Ofri (Weizmann Institute of Science)
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Tuesday, 11.1.2022, 11:30
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Zoom Lecture: https://technion.zoom.us/my/chaimbaskin
While image editing and manipulation tools have seen steady progress, allowing complex editing effects to be achieved by novice users, video editing remains a difficult task: applying edits in a temporally consistent manner to all frames remains a key challenge. In this talk, I’ll present a novel method that tackles this challenge by decomposing an input video into a set of layered 2D atlases, each providing a unified representation of an object/background over the entire ...
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Incorporating Time into Word Representations
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Guy Rosin
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Sunday, 9.1.2022, 14:30
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Zoom Lecture: 99189612386
Our world is constantly evolving, and so is the content on the web. Consequently, our languages, often said to mirror the world, are dynamic in nature. However, most current language representations are static and cannot adapt to changes over time. New words and semantic evolution have been shown to pose a crucial challenge in many Natural Language Processing and Information Retrieval tasks, leading to a significant performance drop for modern language models. In this thesis, ...
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Incentive-Aligned Strategic Classification
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Sagi Levanon
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Sunday, 9.1.2022, 11:30
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Zoom Lecture: 74825775795
Predictive machine learning tools are increasingly being used to inform decisions regarding humans. When human users stand to gain from certain predictive outcomes, they may be prone to act strategically to improve those outcomes. We argue that in many realistic scenarios the system and its users are in fact aligned in their goals. In this work, we give concrete real-world examples for such environments and demonstrate using a series of experiments that they are incentive-aligned. ...
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CS LECTURE: Sublinear-time Graph Algorithms: Motif Counting and Uniform Sampling
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Talya Eden (MIT and Boston University)
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Sunday, 9.1.2022, 10:30
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Room 012 Taub Bld (Learning Center Auditorium)
In this talk I will survey recent developments in approximate subgraph-counting and subgraph-sampling in sublinear-time. Counting and sampling small subgraphs (aka motifs) are two of the most basic primitives in graph analysis, and have been studied extensively, both in theory and in practice. In my talk, I will present the sublinear-time computational model, where access to the input graph is given only through queries, and will explain some of the concepts that underlie my results. ...
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Practical WEB Development Workshop: To Code of Not to Code
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Wednesday, 5.1.2022, 18:30
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Zoom Event: Registration
You are invited to a practical web development workshop that will include an overview of the latest technologies of web application development and practical practice with a demonstration, with the help of Uri Shaked, Voiding warranties at Wokwi.com. The workshop will take place on Wednesday, January 5, 18:30, in a zoom session, and it is optional but not required to be familiar with at least one programming language such as JavaScript, React, Next.js, as well ...
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Theory Seminar: On the Complexity of Two-Party Differential Privacy
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Eliad Tsfadia (Tel-Aviv University) - CANCELLED!
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Wednesday, 5.1.2022, 12:30
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Taub 201 Taub Bld.
In distributed differential privacy, the parties perform analysis over their joint data while preserving the privacy for both datasets. Interestingly, for a few fundamental two-party functions such as inner product and Hamming distance, the accuracy of the distributed solution lags way behind what is achievable in the client-server setting. McGregor, Mironov, Pitassi, Reingold, Talwar, and Vadhan [FOCS ’10] proved that this gap is inherent, showing upper bounds on the accuracy of (any) distributed solution for ...
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Estimating NLP Domain Adaptation Performance Using Model Causal Analysis
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Boaz Ben-Dov
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Tuesday, 4.1.2022, 14:30
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Zoom Lecture: 97209155707
Domain adaptation setups were not all born equal, and some domains are easier to adapt to and from than others. This talk will show and attempt to estimate the difficulty (or ease) of adapting between different domains, based on the causal effect of certain features in the data on the adapting model’s predictions. This question is relevant in many real-life scenarios where computational resources exist in relative abundance, while labeling and data-gathering is time-consuming, expensive ...
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Pixel Club: Computational Imagingfor Sensing High-speed Phenomena
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Mark Sheinin (Carnegie Mellon University)
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Tuesday, 4.1.2022, 13:30
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Zoom Lecture: 9245008892
Despite recent advances in sensor technology, capturing high-speed video at high-spatial resolutionsremains a challenge. This is because, in a conventional camera, the available bandwidth limits either the maximum sampling frequency or thecaptured spatial resolution. In this talk, I am going to cover our recent works that use computational imaging to allow high-speed high-resolution imagingunder certain conditions. First I will describe Diffraction Line Imaging, a novel imaging principle that combines diffractive optics with 1D (line) sensorsto ...
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CS LECTURE: Informed Data Science
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Amir Gilad (Duke University)
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Tuesday, 4.1.2022, 10:30
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Room 012 Taub Bld (Learning Center Auditorium)
Data science has become prevalent in various fields that affect day-to-day lives, such as healthcare, banking, and the job market. The process of developing data science applications usually consists of several automatic systems that manipulate and prepare the data in different manners. Examples of automatic data manipulations and preparations include generating synthetic data, interactive data exploration, repairing the data, and labeling it for machine learning. These systems can be highly complex and even data scientists ...
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CS LECTURE: On the Role of Data in Algorithm Design
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Tal Wagner (Microsoft Research Redmond)
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Sunday, 2.1.2022, 12:30
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Room 012 Taub Bld (Learning Center Auditorium)
Recently, there has been a growing interest in harnessing the power of big datasets and modern machine learning for designing new scalable algorithms. This invites us to rethink the role of data in algorithm design: not just as the input to pre-designed algorithms, but also a factor that enters the algorithm design process itself, driving it in a strong and possibly automated manner. This talk will show how to leverage data and learning for better ...
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