3,414 results on '"Boyarski, A."'
Search Results
2. Data-driven modeling of interrelated dynamical systems
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Yonatan Elul, Eyal Rozenberg, Amit Boyarski, Yael Yaniv, Assaf Schuster, and Alex M. Bronstein
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Astrophysics ,QB460-466 ,Physics ,QC1-999 - Abstract
Abstract Non-linear dynamical systems describe numerous real-world phenomena, ranging from the weather, to financial markets and disease progression. Individual systems may share substantial common information, for example patients’ anatomy. Lately, deep-learning has emerged as a leading method for data-driven modeling of non-linear dynamical systems. Yet, despite recent breakthroughs, prior works largely ignored the existence of shared information between different systems. However, such cases are quite common, for example, in medicine: we may wish to have a patient-specific model for some disease, but the data collected from a single patient is usually too small to train a deep-learning model. Hence, we must properly utilize data gathered from other patients. Here, we explicitly consider such cases by jointly modeling multiple systems. We show that the current single-system models consistently fail when trying to learn simultaneously from multiple systems. We suggest a framework for jointly approximating the Koopman operators of multiple systems, while intrinsically exploiting common information. We demonstrate how we can adapt to a new system using order-of-magnitude less new data and show the superiority of our model over competing methods, in terms of both forecasting ability and statistical fidelity, across chaotic, cardiac, and climate systems.
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- 2024
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3. Distributed learning in congested environments with partial information
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Leshem, Amir, Krishnamurthy, Vikram, and Boyarski, Tomer
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- 2024
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4. Weisfeiler and Leman Go Infinite: Spectral and Combinatorial Pre-Colorings
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Feldman, Or, Boyarski, Amit, Feldman, Shai, Kogan, Dani, Mendelson, Avi, and Baskin, Chaim
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Computer Science - Machine Learning ,Computer Science - Data Structures and Algorithms - Abstract
Graph isomorphism testing is usually approached via the comparison of graph invariants. Two popular alternatives that offer a good trade-off between expressive power and computational efficiency are combinatorial (i.e., obtained via the Weisfeiler-Leman (WL) test) and spectral invariants. While the exact power of the latter is still an open question, the former is regularly criticized for its limited power, when a standard configuration of uniform pre-coloring is used. This drawback hinders the applicability of Message Passing Graph Neural Networks (MPGNNs), whose expressive power is upper bounded by the WL test. Relaxing the assumption of uniform pre-coloring, we show that one can increase the expressive power of the WL test ad infinitum. Following that, we propose an efficient pre-coloring based on spectral features that provably increase the expressive power of the vanilla WL test. The above claims are accompanied by extensive synthetic and real data experiments. The code to reproduce our experiments is available at https://github.com/TPFI22/Spectral-and-Combinatorial
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- 2022
5. Medium Access Control protocol for Collaborative Spectrum Learning in Wireless Networks
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Boyarski, Tomer, Wang, Wenbo, and Leshem, Amir
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Computer Science - Networking and Internet Architecture ,Computer Science - Machine Learning ,Computer Science - Multiagent Systems - Abstract
In recent years there is a growing effort to provide learning algorithms for spectrum collaboration. In this paper we present a medium access control protocol which allows spectrum collaboration with minimal regret and high spectral efficiency in highly loaded networks. We present a fully-distributed algorithm for spectrum collaboration in congested ad-hoc networks. The algorithm jointly solves both the channel allocation and access scheduling problems. We prove that the algorithm has an optimal logarithmic regret. Based on the algorithm we provide a medium access control protocol which allows distributed implementation of the algorithm in ad-hoc networks. The protocol utilizes single-channel opportunistic carrier sensing to carry out a low-complexity distributed auction in time and frequency. We also discuss practical implementation issues such as bounded frame size and speed of convergence. Computer simulations comparing the algorithm to state-of-the-art distributed medium access control protocols show the significant advantage of the proposed scheme.
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- 2021
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6. Distributed learning in congested environments with partial information
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Boyarski, Tomer, Leshem, Amir, and Krishnamurthy, Vikram
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Computer Science - Multiagent Systems - Abstract
How can non-communicating agents learn to share congested resources efficiently? This is a challenging task when the agents can access the same resource simultaneously (in contrast to multi-agent multi-armed bandit problems) and the resource valuations differ among agents. We present a fully distributed algorithm for learning to share in congested environments and prove that the agents' regret with respect to the optimal allocation is poly-logarithmic in the time horizon. Performance in the non-asymptotic regime is illustrated in numerical simulations. The distributed algorithm has applications in cloud computing and spectrum sharing. Keywords: Distributed learning, congestion games, poly-logarithmic regret.
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- 2021
7. Improving Continuous-time Conflict Based Search
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Andreychuk, Anton, Yakovlev, Konstantin, Boyarski, Eli, and Stern, Roni
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Computer Science - Artificial Intelligence ,Computer Science - Multiagent Systems - Abstract
Conflict-Based Search (CBS) is a powerful algorithmic framework for optimally solving classical multi-agent path finding (MAPF) problems, where time is discretized into the time steps. Continuous-time CBS (CCBS) is a recently proposed version of CBS that guarantees optimal solutions without the need to discretize time. However, the scalability of CCBS is limited because it does not include any known improvements of CBS. In this paper, we begin to close this gap and explore how to adapt successful CBS improvements, namely, prioritizing conflicts (PC), disjoint splitting (DS), and high-level heuristics, to the continuous time setting of CCBS. These adaptions are not trivial, and require careful handling of different types of constraints, applying a generalized version of the Safe interval path planning (SIPP) algorithm, and extending the notion of cardinal conflicts. We evaluate the effect of the suggested enhancements by running experiments both on general graphs and $2^k$-neighborhood grids. CCBS with these improvements significantly outperforms vanilla CCBS, solving problems with almost twice as many agents in some cases and pushing the limits of multiagent path finding in continuous-time domains., Comment: This is a pre-print of the paper accepted to AAAI 2021
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- 2021
8. Optimally Solving the Multiple Watchman Route Problem with Heuristic Search.
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Yaakov Livne, Dor Atzmon, Shawn Skyler, Eli Boyarski, Amir Shapiro, and Ariel Felner
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- 2023
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9. Sea-level changes and paleoenvironmental responses in a coastal Florida salt marsh over the last three centuries
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Seitz, Carina, Kenney, William F., Patterson-Boyarski, Brittany, Curtis, Jason H., Vélez, María I., Glodzik, Katie, Escobar, Jaime, and Brenner, Mark
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- 2023
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10. Spectral Geometric Matrix Completion
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Boyarski, Amit, Vedula, Sanketh, and Bronstein, Alex
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Computer Science - Machine Learning ,Computer Science - Computational Geometry ,Computer Science - Computer Vision and Pattern Recognition ,Statistics - Machine Learning - Abstract
Deep Matrix Factorization (DMF) is an emerging approach to the problem of matrix completion. Recent works have established that gradient descent applied to a DMF model induces an implicit regularization on the rank of the recovered matrix. In this work we interpret the DMF model through the lens of spectral geometry. This allows us to incorporate explicit regularization without breaking the DMF structure, thus enjoying the best of both worlds. In particular, we focus on matrix completion problems with underlying geometric or topological relations between the rows and/or columns. Such relations are prevalent in matrix completion problems that arise in many applications, such as recommender systems and drug-target interaction. Our contributions enable DMF models to exploit these relations, and make them competitive on real benchmarks, while exhibiting one of the first successful applications of deep linear networks., Comment: Accepted to Mathematical and Scientific Machine Learning (MSML) 2021 https://msml21.github.io/
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- 2019
11. Electrochemical characterization of a dual cytochrome-containing lactate dehydrogenase
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Boyarski, Anastasya, Shlush, Noam, Paz, Shiraz, Eichler, Jerry, and Alfonta, Lital
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- 2023
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12. Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks
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Stern, Roni, Sturtevant, Nathan, Felner, Ariel, Koenig, Sven, Ma, Hang, Walker, Thayne, Li, Jiaoyang, Atzmon, Dor, Cohen, Liron, Kumar, T. K. Satish, Boyarski, Eli, and Bartak, Roman
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Computer Science - Artificial Intelligence ,Computer Science - Multiagent Systems ,Computer Science - Robotics - Abstract
The MAPF problem is the fundamental problem of planning paths for multiple agents, where the key constraint is that the agents will be able to follow these paths concurrently without colliding with each other. Applications of MAPF include automated warehouses and autonomous vehicles. Research on MAPF has been flourishing in the past couple of years. Different MAPF research papers make different assumptions, e.g., whether agents can traverse the same road at the same time, and have different objective functions, e.g., minimize makespan or sum of agents' actions costs. These assumptions and objectives are sometimes implicitly assumed or described informally. This makes it difficult to establish appropriate baselines for comparison in research papers, as well as making it difficult for practitioners to find the papers relevant to their concrete application. This paper aims to fill this gap and support researchers and practitioners by providing a unifying terminology for describing common MAPF assumptions and objectives. In addition, we also provide pointers to two MAPF benchmarks. In particular, we introduce a new grid-based benchmark for MAPF, and demonstrate experimentally that it poses a challenge to contemporary MAPF algorithms., Comment: Accepted to SoCS 2019: The 12th Annual Symposium on Combinatorial Search
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- 2019
13. Online Multi-Agent Path Finding: New Results.
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Jonathan Morag, Ariel Felner, Roni Stern, Dor Atzmon, and Eli Boyarski
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- 2022
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14. On Merging Agents in Multi-Agent Pathfinding Algorithms.
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Eli Boyarski, Shao-Hung Chan, Dor Atzmon, Ariel Felner, and Sven Koenig
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- 2022
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15. Optimally Solving the Multiple Watchman Route Problem with Heuristic Search (Extended Abstract).
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Yaakov Livne, Dor Atzmon, Shawn Skyler, Eli Boyarski, Amir Shapiro, and Ariel Felner
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- 2022
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16. Subspace Least Squares Multidimensional Scaling
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Boyarski, Amit, Bronstein, Alex M., and Bronstein, Michael M.
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Computer Science - Computational Geometry - Abstract
Multidimensional Scaling (MDS) is one of the most popular methods for dimensionality reduction and visualization of high dimensional data. Apart from these tasks, it also found applications in the field of geometry processing for the analysis and reconstruction of non-rigid shapes. In this regard, MDS can be thought of as a \textit{shape from metric} algorithm, consisting of finding a configuration of points in the Euclidean space that realize, as isometrically as possible, some given distance structure. In the present work we cast the least squares variant of MDS (LS-MDS) in the spectral domain. This uncovers a multiresolution property of distance scaling which speeds up the optimization by a significant amount, while producing comparable, and sometimes even better, embeddings., Comment: Scale Space and Variational Methods in Computer Vision: 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017
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- 2017
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17. Efficient Deformable Shape Correspondence via Kernel Matching
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Lähner, Zorah, Vestner, Matthias, Boyarski, Amit, Litany, Or, Slossberg, Ron, Remez, Tal, Rodolà, Emanuele, Bronstein, Alex, Bronstein, Michael, Kimmel, Ron, and Cremers, Daniel
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Computer Science - Computer Vision and Pattern Recognition - Abstract
We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-wise and point-wise descriptors, imposing a continuity prior on the mapping, and propose a projected descent optimization procedure inspired by difference of convex functions (DC) programming. Surprisingly, in spite of the highly non-convex nature of the resulting quadratic assignment problem, our method converges to a semantically meaningful and continuous mapping in most of our experiments, and scales well. We provide preliminary theoretical analysis and several interpretations of the method., Comment: Accepted for oral presentation at 3DV 2017, including supplementary material
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- 2017
18. Inspiring Computer Vision System Solutions
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Zilly, Julian, Boyarski, Amit, Carvalho, Micael, Abarghouei, Amir Atapour, Amplianitis, Konstantinos, Krasnov, Aleksandr, Mancini, Massimiliano, Gonzalez, Hernán, Spezialetti, Riccardo, Pérez, Carlos Sampedro, and Li, Hao
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Computers and Society - Abstract
The "digital Michelangelo project" was a seminal computer vision project in the early 2000's that pushed the capabilities of acquisition systems and involved multiple people from diverse fields, many of whom are now leaders in industry and academia. Reviewing this project with modern eyes provides us with the opportunity to reflect on several issues, relevant now as then to the field of computer vision and research in general, that go beyond the technical aspects of the work. This article was written in the context of a reading group competition at the week-long International Computer Vision Summer School 2017 (ICVSS) on Sicily, Italy. To deepen the participants understanding of computer vision and to foster a sense of community, various reading groups were tasked to highlight important lessons which may be learned from provided literature, going beyond the contents of the paper. This report is the winning entry of this guided discourse (Fig. 1). The authors closely examined the origins, fruits and most importantly lessons about research in general which may be distilled from the "digital Michelangelo project". Discussions leading to this report were held within the group as well as with Hao Li, the group mentor., Comment: 5 pages. 3 figures
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- 2017
19. Modifying Optimal SAT-based Approach to Multi-agent Path-finding Problem to Suboptimal Variants
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Surynek, Pavel, Felner, Ariel, Stern, Roni, and Boyarski, Eli
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Computer Science - Artificial Intelligence - Abstract
In multi-agent path finding (MAPF) the task is to find non-conflicting paths for multiple agents. In this paper we focus on finding suboptimal solutions for MAPF for the sum-of-costs variant. Recently, a SAT-based approached was developed to solve this problem and proved beneficial in many cases when compared to other search-based solvers. In this paper, we present SAT-based unbounded- and bounded-suboptimal algorithms and compare them to relevant algorithms. Experimental results show that in many case the SAT-based solver significantly outperforms the search-based solvers.
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- 2017
20. Spectral Geometric Matrix Completion.
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Amit Boyarski, Sanketh Vedula, and Alexander M. Bronstein
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- 2021
21. Experimental Evaluation of Classical Multi Agent Path Finding Algorithms.
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Omri Kaduri, Eli Boyarski, and Roni Stern
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- 2021
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22. Improving Continuous-time Conflict Based Search.
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Anton Andreychuk, Konstantin S. Yakovlev, Eli Boyarski, and Roni Stern
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- 2021
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23. f-Aware Conflict Prioritization & Improved Heuristics For Conflict-Based Search.
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Eli Boyarski, Ariel Felner, Pierre Le Bodic, Daniel Damir Harabor, Peter J. Stuckey, and Sven Koenig
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- 2021
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24. Multidimensional Scaling
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Boyarski, Amit, Bronstein, Alex, and Ikeuchi, Katsushi, editor
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- 2021
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25. Iterative-Deepening Conflict-Based Search.
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Eli Boyarski, Ariel Felner, Daniel Harabor, Peter J. Stuckey, Liron Cohen 0002, Jiaoyang Li 0001, and Sven Koenig
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- 2020
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26. Algorithm Selection for Optimal Multi-Agent Pathfinding.
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Omri Kaduri, Eli Boyarski, and Roni Stern
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- 2020
27. Spectral Subgraph Localization.
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Ama Bembua Bainson, Judith Hermanns, Petros Petsinis, Niklas Aavad, Casper Dam Larsen, Tiarnan Swayne, Amit Boyarski, Davide Mottin, Alex M. Bronstein, and Panagiotis Karras
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- 2023
28. Multiple broods, simultaneous nests, and autumn nesting by Costa's Hummingbirds ( Calypte costae )
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Boyarski, Dave, Batchelder, Ned, Batchelder, Gigi, DeRoss, Mary Jane, DeRoss, Dennis, Thomason, Lynne, Thomason, Gary, Hendricks, Paul, and Marks, Jeffrey S.
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- 2020
29. Further Improved Heuristics For Conflict-Based Search.
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Eli Boyarski, Ariel Felner, Pierre Le Bodic, Daniel Harabor, Peter J. Stuckey, and Sven Koenig
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- 2021
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30. Studying Online Multi-Agent Path Finding.
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Jonathan Morag, Roni Stern, Ariel Felner, Dor Atzmon, and Eli Boyarski
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- 2021
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31. Shape Correspondence with Isometric and Non-Isometric Deformations.
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Roberto M. Dyke, C. Stride, Yu-Kun Lai, Paul L. Rosin, Mathieu Aubry, Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers, Matthew Fisher, Thibault Groueix, Daoliang Guo, Vladimir G. Kim, Ron Kimmel, Zorah Lähner, Kun Li 0001, Or Litany, Tal Remez, Emanuele Rodolà, Bryan C. Russell, Yusuf Sahillioglu, Ron Slossberg, Gary K. L. Tam, Matthias Vestner, Z. Wu, and Jingyu Yang 0002
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- 2019
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32. Improved Heuristics for Multi-Agent Path Finding with Conflict-Based Search.
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Jiaoyang Li 0001, Ariel Felner, Eli Boyarski, Hang Ma 0001, and Sven Koenig
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- 2019
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33. Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks.
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Roni Stern, Nathan R. Sturtevant, Ariel Felner, Sven Koenig, Hang Ma 0001, Thayne T. Walker, Jiaoyang Li 0001, Dor Atzmon, Liron Cohen 0002, T. K. Satish Kumar, Roman Barták, and Eli Boyarski
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- 2019
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34. The Physics of the B Factories
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Bevan, A. J., Golob, B., Mannel, Th., Prell, S., Yabsley, B. D., Abe, K., Aihara, H., Anulli, F., Arnaud, N., Aushev, T., Beneke, M., Beringer, J., Bianchi, F., Bigi, I. I., Bona, M., Brambilla, N., rodzicka, J. B, Chang, P., Charles, M. J., Cheng, C. H., Cheng, H. -Y., Chistov, R., Colangelo, P., Coleman, J. P., Drutskoy, A., Druzhinin, V. P., Eidelman, S., Eigen, G., Eisner, A. M., Faccini, R., Flood, K. T ., Gambino, P., Gaz, A., Gradl, W., Hayashii, H., Higuchi, T., Hulsbergen, W. D., Hurth, T., Iijima, T., Itoh, R., Jackson, P. D., Kass, R., Kolomensky, Yu. G., Kou, E., Križan, P., Kronfeld, A., Kumano, S., Kwon, Y. J., Latham, T. E., Leith, D. W. G. S., Lüth, V., Martinez-Vidal, F., Meadows, B. T., Mussa, R., Nakao, M., Nishida, S., Ocariz, J., Olsen, S. L., Pakhlov, P., Pakhlova, G., Palano, A., Pich, A., Playfer, S., Poluektov, A., Porter, F. C., Robertson, S. H., Roney, J. M., Roodman, A., Sakai, Y., Schwanda, C., Schwartz, A. J., Seidl, R., Sekula, S. J., Steinhauser, M., Sumisawa, K., Swanson, E. S., Tackmann, F., Trabelsi, K., Uehara, S., Uno, S., van der Water, R., Vasseur, G., Verkerke, W., Waldi, R., Wang, M. Z., Wilson, F. F., Zupan, J., Zupanc, A., Adachi, I., Albert, J., Banerjee, Sw., Bellis, M., Ben-Haim, E., Biassoni, P., Cahn, R. N., Cartaro, C., Chauveau, J., Chen, C., Chiang, C. C., Cowan, R., Dalseno, J., Davier, M., Davies, C., Dingfelder, J. C., nard, B. Eche, Epifanov, D., Fulsom, B. G., Gabareen, A. M., Gary, J. W., Godang, R., Graham, M. T., Hafner, A., Hamilton, B., Hartmann, T., Hayasaka, K., Hearty, C., Iwasaki, Y., Khodjamirian, A., Kusaka, A., Kuzmin, A., Lafferty, G. D., Lazzaro, A., Li, J., Lindemann, D., Long, O., Lusiani, A., Marchiori, G., Martinelli, M., Miyabayashi, K., Mizuk, R., Mohanty, G. B., Muller, D. R., Nakazawa, H., Ongmongkolkul, P., Pacetti, S., Palombo, F., Pedlar, T. K., Piilonen, L. E., Pilloni, A., Poireau, V., Prothmann, K., Pulliam, T., Rama, M., Ratcliff, B. N., Roudeau, P., Schrenk, S., Schroeder, T., Schubert, K. R., Shen, C. P., Shwartz, B., Soffer, A., Solodov, E. P., Somov, A., Starič, M., Stracka, S., Telnov, A. V., Todyshev, K. Yu., Tsuboyama, T., Uglov, T., Vinokurova, A., Walsh, J. J., Watanabe, Y., Won, E., Wormser, G., Wright, D. H., Ye, S., Zhang, C. C., Abachi, S., Abashian, A., Abe, N., Abe, R., Abe, T., Abrams, G. S., Adam, I., Adamczyk, K., Adametz, A., Adye, T., Agarwal, A., Ahmed, H., Ahmed, M., Ahmed, S., Ahn, B. S., Ahn, H. S., Aitchison, I. J. R., Akai, K., Akar, S., Akatsu, M., Akemoto, M., Akhmetshin, R., Akre, R., Alam, M. S., Albert, J. N., Aleksan, R., Alexander, J. P., Alimonti, G., Allen, M. T., Allison, J., Allmendinger, T., Alsmiller, J. R. G., Altenburg, D., Alwyn, K. E., An, Q., Anderson, J., Andreassen, R., Andreotti, D., Andreotti, M., Andress, J. C., Angelini, C., Anipko, D., Anjomshoaa, A., Anthony, P. L., Antillon, E. A., Antonioli, E., Aoki, K., Arguin, J. F., Arinstein, K., Arisaka, K., Asai, K., Asai, M., Asano, Y., Asgeirsson, D. J., Asner, D. M., Aso, T., Aspinwall, M. L., Aston, D., Atmacan, H., Aubert, B., Aulchenko, V., Ayad, R., Azemoon, T., Aziz, T., Azzolini, V., Azzopardi, D. E., Baak, M. A., Back, J. J., Bagnasco, S., Bahinipati, S., Bailey, D. S., Bailey, S., Bailly, P., van Bakel, N., Bakich, A. M., Bala, A., Balagura, V., Baldini-Ferroli, R., Ban, Y., Banas, E., Band, H. R., Banerjee, S., Baracchini, E., Barate, R., Barberio, E., Barbero, M., Bard, D. J., Barillari, T., Barlow, N. R., Barlow, R. J., Barrett, M., Bartel, W., Bartelt, J., Bartoldus, R., Batignani, G., Battaglia, M., Bauer, J. M., Bay, A., Beaulieu, M., Bechtle, P., Beck, T. W., Becker, J., Becla, J., Bedny, I., Behari, S., Behera, P. K., Behn, E., Behr, L., Beigbeder, C., Beiline, D., Bell, R., Bellini, F., Bellodi, G., Belous, K., Benayoun, M., Benelli, G., Benitez, J. F., Benkebil, M., Berger, N., Bernabeu, J., Bernard, D., Bernet, R., Bernlochner, F. U., Berryhill, J. W., Bertsche, K., Besson, P., Best, D. S., Bettarini, S., Bettoni, D., Bhardwaj, V., Bhimji, W., Bhuyan, B., Biagini, M. E., Biasini, M., van Bibber, K., Biesiada, J., Bingham, I., Bionta, R. M., Bischofberger, M., Bitenc, U., Bizjak, I., Blanc, F., Blaylock, G., Blinov, V. E., Bloom, E., Bloom, P. C., Blount, N. L., Blouw, J., Bly, M., Blyth, S., Boeheim, C. T., Bomben, M., Bondar, A., Bondioli, M., Bonneaud, G. R., Bonvicini, G., Booke, M., Booth, J., Borean, C., Borgland, A. W., Borsato, E., Bosi, F., Bosisio, L., Botov, A. A., Bougher, J., Bouldin, K., Bourgeois, P., Boutigny, D., Bowerman, D. A., Boyarski, A. M., Boyce, R. F., Boyd, J. T., Bozek, A., Bozzi, C., Bračko, M., Brandenburg, G., Brandt, T., Brau, B., Brau, J., Breon, A. B., Breton, D., Brew, C., Briand, H., Bright-Thomas, P. G., Brigljević, V., Britton, D. I., Brochard, F., Broomer, B., Brose, J., Browder, T. E., Brown, C. L., Brown, C. M., Brown, D. N., Browne, M., Bruinsma, M., Brunet, S., Bucci, F., Buchanan, C., Buchmueller, O. L., Bünger, C., Bugg, W., Bukin, A. D., Bula, R., Bulten, H., Burchat, P. R., Burgess, W., Burke, J. P., Button-Shafer, J., Buzykaev, A. R., Buzzo, A., Cai, Y., Calabrese, R., Calcaterra, A., Calderini, G., Camanzi, B., Campagna, E., Campagnari, C., Capra, R., Carassiti, V., Carpinelli, M., Carroll, M., Casarosa, G., Casey, B. C. K., Cason, N. M., Castelli, G., Cavallo, N., Cavoto, G., Cecchi, A., Cenci, R., Cerizza, G., Cervelli, A., Ceseracciu, A., Chai, X., Chaisanguanthum, K. S., Chang, M. C., Chang, Y. H., Chang, Y. W., Chao, D. S., Chao, M., Chao, Y., Charles, E., Chavez, C. A., Cheaib, R., Chekelian, V., Chen, A., Chen, E., Chen, G. P., Chen, H. F., Chen, J. -H., Chen, J. C., Chen, K. F., Chen, P., Chen, S., Chen, W. T., Chen, X., Chen, X. R., Chen, Y. Q., Cheng, B., Cheon, B. G., Chevalier, N., Chia, Y. M., Chidzik, S., Chilikin, K., Chistiakova, M. V., Cizeron, R., Cho, I. S., Cho, K., Chobanova, V., Choi, H. H. F., Choi, K. S., Choi, S. K., Choi, Y., Choi, Y. K., Christ, S., Chu, P. H., Chun, S., Chuvikov, A., Cibinetto, G., Cinabro, D., Clark, A. R., Clark, P. J., Clarke, C. K., Claus, R., Claxton, B., Clifton, Z. C., Cochran, J., Cohen-Tanugi, J., Cohn, H., Colberg, T., Cole, S., Colecchia, F., Condurache, C., Contri, R., Convert, P., Convery, M. R., Cooke, P., Copty, N., Cormack, C. M., Corso, F. Dal, Corwin, L. A., Cossutti, F., Cote, D., Ramusino, A. Cotta, Cottingham, W. N., Couderc, F., Coupal, D. P., Covarelli, R., Cowan, G., Craddock, W. W., Crane, G., Crawley, H. B., Cremaldi, L., Crescente, A., Cristinziani, M., Crnkovic, J., Crosetti, G., Cuhadar-Donszelmann, T., Cunha, A., Curry, S., D'Orazio, A., Dû, S., Dahlinger, G., Dahmes, B., Dallapiccola, C., Danielson, N., Danilov, M., Das, A., Dash, M., Dasu, S., Datta, M., Daudo, F., Dauncey, P. D., David, P., Davis, C. L., Day, C. 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M., Zhulanov, V., Ziegler, T., Ziegler, V., Zioulas, G., Zisman, M., Zito, M., Zürcher, D., Zwahlen, N., Zyukova, O., Živko, T., and Žontar, D.
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High Energy Physics - Experiment ,High Energy Physics - Phenomenology - Abstract
This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C. Please note that version 3 on the archive is the auxiliary version of the Physics of the B Factories book. This uses the notation alpha, beta, gamma for the angles of the Unitarity Triangle. The nominal version uses the notation phi_1, phi_2 and phi_3. Please cite this work as Eur. Phys. J. C74 (2014) 3026., Comment: 928 pages, version 3 (arXiv:1406.6311v3) corresponds to the alpha, beta, gamma version of the book, the other versions use the phi1, phi2, phi3 notation
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- 2014
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35. Quantification of phenolic compounds, antioxidant power and sugar content in commercial products based on Camellia sinensis L./Quantificacao de compostos fenolicos, poder antioxidante e teor de acucares em produtos comerciais a base de Camellia sinensis L
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de Macena, Thássia Fernandes Santana, Boyarski, Daiara RakeliSimao, Barbosa, Denise Rocha Ramos, and Clemente, Rodolfo Castilho
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- 2020
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36. Adding Heuristics to Conflict-Based Search for Multi-Agent Path Finding.
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Ariel Felner, Jiaoyang Li 0001, Eli Boyarski, Hang Ma 0001, Liron Cohen 0002, T. K. Satish Kumar, and Sven Koenig
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- 2018
37. Sub-Optimal SAT-Based Approach to Multi-Agent Path-Finding Problem.
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Pavel Surynek, Ariel Felner, Roni Stern, and Eli Boyarski
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- 2018
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38. Variants of Independence Detection in SAT-Based Optimal Multi-agent Path Finding
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Surynek, Pavel, Švancara, Jiří, Felner, Ariel, Boyarski, Eli, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, van den Herik, Jaap, editor, Rocha, Ana Paula, editor, and Filipe, Joaquim, editor
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- 2018
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39. Collaborating Center on Food and School Nutrition (CECANE/UFT) in state of Tocantins
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Lisandra Lustoza Ferro, Claudia Jaqueline Fialho, Renata Andrade de Medeiros Moreira, Daiara Rakeli Simão Boyarski, Dayane Justos dos Santos, Izabela Ribeiro Rodrigues, and Mariana de Menezes
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Alimentação Escolar ,Programa Nacional de Alimentação Escolar ,Formação de Atores Sociais do PNAE ,Segurança Alimentar e Nutricional ,Agricultura Familiar ,Medicine ,Science ,Social Sciences - Abstract
The Collaborating Center on Food and School Nutrition (CECANE) are partnerships between the National Fund for the Development of Education (FNDE) and Federal Institutions for Higher Education, which intend to provide technical and operational support to the implementation of the National School Feeding Program (PNAE), in order to guarantee the supply of adequate and healthy food to the students of public and philanthropic schools. Among the activities implemented by CECANE of the Federal University of Tocantins (UFT), it is worth noting the advising and monitoring of 36 municipalities in the years 2016 to 2017, contributing to the training of human resources responsible for PNAE and data collection on execution. It is concluded that there is a need for the continuation of CECANE / UFT actions, in order to continuously serve the largest number of municipalities and social actors of the PNAE, in order to promote the effective execution of the PNAE.
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- 2019
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40. Multidimensional Scaling
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Boyarski, Amit, primary and Bronstein, Alex, additional
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- 2020
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41. Modeling and Solving the Multi-agent Pathfinding Problem in Picat.
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Roman Barták, Neng-Fa Zhou, Roni Stern, Eli Boyarski, and Pavel Surynek
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- 2017
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42. Search-Based Optimal Solvers for the Multi-Agent Pathfinding Problem: Summary and Challenges.
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Ariel Felner, Roni Stern, Solomon Eyal Shimony, Eli Boyarski, Meir Goldenberg, Guni Sharon, Nathan R. Sturtevant, Glenn Wagner, and Pavel Surynek
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- 2017
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43. Subspace Least Squares Multidimensional Scaling.
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Amit Boyarski, Alexander M. Bronstein, and Michael M. Bronstein
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- 2017
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44. Variants of Independence Detection in SAT-Based Optimal Multi-agent Path Finding.
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Pavel Surynek, Jiri Svancara, Ariel Felner, and Eli Boyarski
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- 2017
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45. Integration of Independence Detection into SAT-based Optimal Multi-Agent Path Finding - A Novel SAT-based Optimal MAPF Solver.
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Pavel Surynek, Jiri Svancara, Ariel Felner, and Eli Boyarski
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- 2017
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46. Efficient Deformable Shape Correspondence via Kernel Matching.
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Matthias Vestner, Zorah Lähner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, and Daniel Cremers
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- 2017
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47. F-Cardinal Conflicts in Conflict-Based Search.
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Eli Boyarski, Daniel Harabor, Peter J. Stuckey, Pierre Le Bodic, and Ariel Felner
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- 2020
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48. Additives That Prevent Or Reverse Cathode Aging In Drift Chambers With Helium-Isobutane Gas
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Boyarski, Adam
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High Energy Physics - Experiment - Abstract
Noise and Malter breakdown have been studied at high rates in a test chamber having the same cell structure and gas as in the BaBar drift chamber. The chamber was first damaged by exposing it to a high source level at an elevated high voltage, until its operating current at normal voltages was below 0.5nA/cm. Additives such as water or alcohol allowed the damaged chamber to operate at 25 nA/cm, but when the additive was removed the operating point reverted to the original low value. However with 0.02% to 0.05% oxygen or 5% carbon dioxide the chamber could operate at more than 25 nA/cm, and continued to operate at this level even after the additive was removed. This shows for the first time that running with an O2 or CO2 additive at high ionisation levels can cure a damaged chamber from breakdown problems., Comment: There were typos: 0.2%-0.5% oxygen should be 0.02%-0.05% oxygen. Values in the Table were OK
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- 2001
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49. Quantificação de compostos fenólicos, poder antioxidante e teor de açúcares em produtos comerciais a base de Camellia sinensis L.
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Thássia Fernandes Santana de Macena, Daiara Rakeli Simão Boyarski, Denise Rocha Ramos Barbosa, and Rodolfo Castilho Clemente
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camellia sinensis. ação antioxidante. compostos fenólicos. açúcares. chá. ,Agriculture (General) ,S1-972 ,Public aspects of medicine ,RA1-1270 - Abstract
Objective: To analyze and quantitatively compare phenolic compounds, antioxidant capacity and sugars present in infusions and soluble extracts of Camellia sinensis L, Methods: The study presents a completely randomized design, using samples for convenience, Three random samples of each type of tea, The analyzes of total phenolic compounds and flavonoids were determined by the Folin-Ciocalteu colorimetric method and aluminum chloride, respectively, total tannins by complexation with casein and condensates by the butanol-HCl method, The antioxidant capacity, by ferricyanide methodology and free radical scavenging by the radical 2,2-diphenyl-1-picryl-hydrazil, and reducing and non-reducing sugars, through the reagent 3-5 dinitrosalicylic acid, Result: The infused extracts showed significantly higher amounts of total phenolic compounds and flavonoids compared to the soluble, This behavior was the same for tannins and antioxidant activity, The infusions obtained greater reducing power and capacity to reduce free radicals, Soluble extracts were highlighted, with a greater presence of sugars, These results were confirmed by the literature and there were no studies carried out with soluble extracts and methodologies similar to that performed here for comparison, Conclusion: The infusions studied in the present study were richer in bioactive and antioxidant compounds, favoring their benefits for the population, with soluble extracts having a greater presence of additional sugars
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- 2020
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50. Efficient SAT Approach to Multi-Agent Path Finding Under the Sum of Costs Objective.
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Pavel Surynek, Ariel Felner, Roni Stern, and Eli Boyarski
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- 2016
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