optimization

Ahmed Youssef Ragab Radwan

Visiting Student (former), Information Science Lab
Visiting student at the Information Science Lab, in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST)

KAUST Research Workshop on Optimization and Big Data

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B19 L3 H2

The age of "big data" is here: data of unprecedented sizes is becoming ubiquitous, which brings new challenges and new opportunities. With this comes the need to solve optimization problems of unprecedented sizes.

Everything you always wanted to know about single machine large-scale graph analytics

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B9 L2 H1

Abstract: Graphs are a natural way to capture relations among objects or people. This has led to graph processing systems being used in a wide variety of fields, ranging from biology to social networks, and a large number of such systems have been described in the recent literature. The focus of our recent work is on single machine graph processing systems where the graph is processed from main memory or external storage. We perform a systematic comparison of various techniques proposed to speed up in-memory multicore graph processing. In addition, we take an end- to-end view of execution time

Use Mathematics and get a SPARQL Query Engine (almost) for Free! It’s MAGiQ!

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B9 L2 H1 R2322

Existing RDF engines are designed for specific hardware architectures; porting to a different architecture (e.g., GPUs) entails enormous implementation effort. We explore sparse matrix algebra as an alternative for designing a portable, scalable and efficient RDF engine.

Langevin Monte Carlo as an optimization algorithm

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B9 L2 H1 R2322

Adil Salim is mainly interested in stochastic approximation, optimization, and machine learning. He is currently a Postdoctoral Research Fellow working with Professor Peter Richtarik at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST).

Space-Time Tomographic Reconstruction of Deforming Objects

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B1 L2 R2202

In this thesis, a variety of applications in computer vision and graphics of inverse problems using tomographic imaging modalities will be presented: (i) The first application focuses on the CT reconstruction with a specific emphasis on recovering thin 1D and 2D manifolds embedded in 3D volumes. (ii) The second application is about space-time tomography (iii) Base on the second application, the third one is aiming to improve the tomographic reconstruction of time-varying geometries undergoing faster, non-periodic deformations, by a warp-and-project strategy. Finally, with a physically plausible divergence-free prior for motion estimation, as well as a novel view synthesis technique, we present applications to dynamic fluid imaging which further demonstrates the flexibility of our optimization frameworks

Optimal Algorithms for Affinely Constrained, Distributed, Decentralized, Minimax, and High-Order Optimization Problems

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B5 R5220

In this thesis, we discuss a few fundamental and well-studied optimization problem classes: decentralized distributed optimization (Chapters 2 to 4), distributed optimization under similarity (Chapter 5), affinely constrained optimization (Chapter 6), minimax optimization (Chapter 7), and high-order optimization (Chapter 8). For each problem class, we develop the first provably optimal algorithm: the complexity of such an algorithm cannot be improved for the problem class given. The proposed algorithms show state-of-the-art performance in practical applications, which makes them highly attractive for potential generalizations and extensions in the future.

Aerial Path Planning for Urban Scene Reconstruction: A Continuous Optimization Method and Benchmark

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Small unmanned aerial vehicles (UAVs) are ideal capturing devices for high-resolution urban 3D reconstructions using multi-view stereo. Nevertheless, practical considerations such as safety usually mean that access to the scan target is often only available for a short amount of time, especially in urban environments. It, therefore, becomes crucial to perform both view and path planning to minimize flight time while ensuring complete and accurate reconstructions. In this work, we address the challenge of automatic view and path planning for UAV-based aerial imaging with the goal of urban

Adel is invited to give a talk in EECVC on "Optimization meets Deep Learning"

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​Adel is invited to give a talk in EECVC on "Optimization meets Deep Learning"​. It is a 45 minutes talk scheduled on the 6th of July 2019.

Accelerating the grapevine effect

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By looking at classical gossip algorithms from a novel perspective, KAUST Professor Peter Richtarik has found a way to significantly speed up gossip-based information sharing, and in the process, he discovered new applications for this efficient mathematical approach. Gossip involves the sharing of information between individuals in a network and can be applied mathematically in both human social networks and data networks, such as distributed sensors. “A network is a collection of nodes, each connected to other nodes via links,” explains Richtarik. “In social networks, for instance

KAUST Professor Peter Richtárik wins Distinguished Speaker Award

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Peter Richtárik, KAUST professor of computer science, recently received a Distinguished Speaker Award at the Sixth International Conference on Continuous Optimization (ICCOPT 2019) held in Berlin from August 3 to 8. ICCOPT 2019 was organized by the Mathematical Optimization Society and was hosted this year by the Weierstrass Institute for Applied Analysis and Stochastics.

Meet KAUST Prospective Student: Igor Sokolov

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Igor Sokolov, 23, is an applied mathematics and physics graduate who will join KAUST from the Moscow Institute of Physics and Technology, Russia. Igor first came to KAUST as a visiting student in 2019 and was highly impressed by the University's living and working facilities. It was this first impression that prompted him to pursue an M.S. at KAUST. Sokolov will join KAUST in the Fall of 2020 as an M.S. candidate under the supervision of Professor Peter Richtarik.

Tariq Alturkestani

Ph.D. Student, Computer Science
Tariq is a PhD student in Computer Science working under the supervision of Professor David E. Keyes. He is working on developing a library that enables users to overlap I/O and compute. Tariq holds a Bachelors degree from Penn State University and a Master from KAUST. Education Profile MS, Computer Science, King Abdullah University of Science and Technology (KAUST), 2014. BS, Computer Science, Penn State University, USA, 2013.

Ramzi Idoughi

Research Scientist, Computer Science
Ramzi Idoughi is a Research Scientist in the Computational Imaging Group (VCCIMAGING) working with Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Ramzi obtained his engineering degree in Space System and Image Processing from National Higher French Institute of Aeronautics and Space (ISAE/SUPAERO) in France in 2011. Later, he received his master degree in Signal, Image, Acoustics and Optimization (SIAO) from Higher Educational Institution in Toulouse (ENSEEIHT) in France in 2011. After that in 2015, he received his doctoral

Peter Richtarik

Professor, Computer Science
Professor Richtárik specializes in big data optimization and machine learning. He is known for his work on randomized coordinate descent algorithms, stochastic gradient descent and federated learning.

Laurent Condat

I am a senior researcher working in optimization, in the group of Prof. Peter Richtárik.

Konstantin Mishchenko

Ph.D. Student, Computer Science
Konstantin Mishchenko is a Ph.D. candidate at Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Peter Richtarik in his research group. Education and Early Career Konstantin Mishchenko obtained his bachelor degree in Computer Science and Physics from Moscow Institute of Physics and Technology in 2016. After that in 2017, he received his master degree in Machine Learning MASH from Université Paris Dauphine in Paris, France. Konstantin had many internships during his studies. The most recent was with Amazon in

Kai Yi

Kai Yi is a Ph.D. candidate in Optimization and Machine Learning Lab led by Professor Peter Richtarik. He received his Computer Science MS from KAUST in Dec. 2021. Before that, he received B.Eng with honor from the Department of Software Engineering, Xi’an Jiaotong University, in June 2019. He has interned at Tencent AI Lab, CMU, NUS, and SenseTime. Research Interest Kai Yi's current research interests include Machine learning optimization in the large-scale data/model era. Conceptual-level knowledge transfer learning: theories and applications. Specifically, he works on machine learning

Guangming Zang

Research Engineer, Computer Science
Guangming Zang is a research engineer in the Computational Imaging Group (VCCIMAGING) under the supervision of Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Guangming obtained his bachelor degree in Software Engineering from China University of Geosciences in Wuhan, China in 2013. He received his master degree in Computer Science from University of Chinese Academy of Sciences in China. Before joining KAUST, Guangming was a research assistant (2013 – 2014) at The National Space Science Center at Chinese Academy of Sciences

Francesco Orabona

Associate Professor, Computer Science
Achieving "parameter-free" machine learning is the primary focus of Professor Francesco Orabona. He is particularly interested in designing superior algorithms to train deep learning models.

El Houcine Bergou

Postdoctoral Research Fellow, ‌InfoCloud
As of January 2019, El Houcine Bergou is a Postdoctoral Research Fellow at Extreme Computing Research Center (ECRC) in King Abdullah University of Science and Technology (KAUST), working with Professor Panagiotis Kalnis in his research group. Prior to this, he spent a year as a Postdoctoral Research Fellow in the Optimization and Machine Learning group of Professor Peter Richtárik. Education and Early Career Dr. Bergou has a PhD degree in numerical methods for least squares problems with application to data assimilation from the National Institute of Posts and Telecommunications (INPT) in

Eric Feron

With 31 years of teaching and research experience, Professor Feron’s work utilizes elementary concepts of control systems, optimization and computer science to address critical issues in modern aerospace engineering and robotics.

Elnur Gasanov

Elnur Gasanov is a master student at Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Peter Richtárik in his research group. Education and Early Career Elnur Gasanov obtained his bachelor degree in Applied Mathematics and Physics from Moscow Institute of Physics and Technology (MIPT) in Moscow, Russia in 2018. Research Interest His research interests are in optimization and machine learning. Education Profile ​B.Sc., Applied Mathematics and Physics, Moscow Institute of Physics and Technology (State

Egor Shulgin

Ph.D. Student, Computer Science
Egor Shulgin is a CS student in the MS/Ph.D. program under the supervision of Professor Peter Richtarik at the Visual Computing Center (VCC) at the King Abdullah University of Science and Technology (KAUST), Saudi Arabia. Education and Early Career Egor obtained his bachelor's degree in Applied Mathematics, Physics, and Computer Science from the Moscow Institute of Physics and Technology (MIPT) in 2019. He first came to KAUST for a research visit in 2019. Later, he joined Prof. Peter Richtarik's group as a MS/Ph.D. student. In 2021 Egor did a research internship with Distributed AI team at the

Dmitry Kovalev

Ph.D. Student, Computer Science
Education Dmitry obtained a B.S. degree from Moscow Institute of Physics and Technology, Moscow, Russia, in 2018. He is an M.S. in the Computer Science program at the King Abdullah University of Science and Technology as of Fall 2018. Publications Dmitry Kovalev, Samuel Horvath and Peter Richtárik. Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop, arXiv preprint arXiv:1901.08689, 2019. Dmitry Kovalev, Peter Richtárik, Eduard Gorbunov, Elnur Gasanov. Stochastic Spectral and Conjugate Descent Methods . Advances in Neural Information Processing

Biao Zhang

Ph.D. Student, Computer Science
Biao Zhang is a Computer Science Ph.D. candidate at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Peter Wonka in his research group. Education and Early Career Biao Zhang obtained his bachelor degree in Mathematics and master degree in Applied Mathematics from Xi’an Jiaotong University in China. Research Interest Biao Zhang is mainly interested in machine learning and computer vision. Education Profile M.S., Applied Mathematics, Xi’an Jiaotong University, China B.S., Mathematics, Xi’an Jiaotong University

Alyazeed Basyoni

M.S. Student, Computer Science
Alyazeed Basyoni is a CS Master Student under the supervision of Professor Peter Richtarik at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST). Education and Early Career Alyazeed joined Carnegie Mellon University in Pittsburgh, Pennsylvania and earned his bachelor degree in Computer Science with minor in Mathematics in 2018. Education Profile B.S., Computer Science, Carnegie Mellon University, USA, 2018

Ali H. AlNasser

M.S. Student, Computer Science
Ali AlNasser is a Masters student in Computer Science. His research interests are scaling deep learning algorithms available now to be used on multicore computers by leveraging the high parallelism in Deep learning. Why KAUST? The abundance of opportunities available in KAUST. Education Profile B.S, Electrical & Computer Engineering, University of Colorado at Boulder. B.S, Applied Mathematics, University of Colorado at Boulder.

Adil Salim

Postdoctoral Research Fellow, Computer Science
Adil Salim is a Postdoctoral Research Fellow working with Professor Peter Richtarik at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Early Career Dr. Salim earned his Master degrees in Data Science and Statistical Engineering from ENSAE ParisTech and in Probability Theory and Stochastic Modeling from Paris XI University in France in 2015. He received his Ph.D. in Machine Learning from Télécom ParisTech in France in 2018. Before joining KAUST, Adil worked in many positions starting from an Auditor for banks and insurance companies