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Design and implementation of large-scale machine learning and computer vision applications. 2014–2016 Research Engineer at the NYU Center for Data Science Development of open source tools for machine learning and data science. 2016–2018 Lecturer in Discipline at Columbia University Teaching in the Data Science Master program,
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the minimum number observations (data points) required to estimate the underlying model parameters. As pointed out by Fischler and Bolles [1], unlike conventional sampling techniques that use as much of the data as possible to obtain an initial solution and then proceed to prune outliers, RANSAC uses the smallest set possible Besides the complexity of IR tasks, such as understanding the user's information needs, a main reason is the lack of high-quality and/or large-scale training data for many IR tasks. This necessitates studying how to design and train machine learning algorithms where there is no large-scale or high-quality data in hand.
The DMP facilitates data management in the VPH-Share project. The DMP supports the data providers with tools to select data to be exposed, semantically annotate the data and securely provide the data to the VPH community by hosting it in the VPH-Share Cloud environment and exposing it via web service, REST and Linked Data interfaces.
I'm an undergrad in Computer Science, Math, and Stats at the University of Toronto. I'm currently a Machine Learning Research Intern at Deep Genomics. I'm also very fortunate to work with David Duvenaud at the Vector Institute. I'm interested in energy-based models, latent variable models, neural ODEs, variational inference, and genomics.
Data science projects could be very long and demanding. From problem framing to model building and application, the process could take weeks and even months, depending on the scale of the problem. As a practicing data scientist, hitting a roadblock with a project is something inevitable.
COS 597J Advanced Topics in Computer Science This seminar prepares computer science graduate students and advanced undergraduate students to effectively engage on matters of public policy and law. The core of the course is a survey of computer science research that has successfully influenced government decision making or commercial practices.
[Sept 2020] I am in the program committee of the third Machine Learning and the Physical Sciences workshop at the Conference Neural Information Processing Systems (NeurIPS) 2020. [July 2020] Full paper titled "Reinforcement Learning-driven Information Seeking: A Quantum Probabilistic Approach" has been accepted in BIRDS, SIGIR 2020 .
Data engineers are software developers that are keen in developing systems around data, making sure those systems scale and perform, that the data is consistent, uniform, recoverable and reliable, and finally, that it is minable. We build scalable platforms for the collection, management, and analysis of data. Technical Skills
Advances in Neural Information Processing Systems (NeurIPS) 27, Montreal, Canada. Pseudo-code and Code for experiments. van Hasselt, H., Mahmood, A. R., Sutton, R. S. (2014). Off-policy TD(λ) with a true online equivalence. In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI), Quebec City, Canada.
In this project, we have addressed the problem of large-scale information integration to enable on-the-fly queries over structured Web data. Uncovering Hidden Web data. Our goal in this project is to develop a scalable infrastructure that automates, to a large extent, the process of discovering, organizing, and extracting data from hidden-Web ...
Year Published: 2019 The National Map—New data delivery homepage, advanced viewer, lidar visualization. As one of the cornerstones of the U.S. Geological Survey’s (USGS) National Geospatial Program, The National Map is a collaborative effort among the USGS and other Federal, State, and local partners to improve and deliver topographic information for the Nation.
In this project, we have addressed the problem of large-scale information integration to enable on-the-fly queries over structured Web data. Uncovering Hidden Web data. Our goal in this project is to develop a scalable infrastructure that automates, to a large extent, the process of discovering, organizing, and extracting data from hidden-Web ...
CPSC: Computer Science. The Department of Computer Science offers several options in first year: CPSC 110 is for students pursuing Computer Science specializations or who plan to take CPSC 210. CPSC 103 targets students desiring an introduction to computing and programming, but with no plans to take further Computer Science courses.
This model was trained from scratch with 5000 images (no data augmentation) and scored a dice coefficient of 0.988423 (511 out of 735) on over 100k test images. This score could be improved with more training, data augmentation, fine tuning, playing with CRF post-processing, and applying more weights on the edges of the masks.
(10/20) Gave a keynote talk titled Collaborative Interdisciplinary ML-Centric Data Analytics at Scale at NDBC 2020. (9/20) Check our Amber video and Texer demo video at VLDB 2020. (7/20) Paper titled "Beanstalk: A General Cost-Based Optimizer Framework for Incremental Data Processing" accepted by VLDB 2021.
CSE 511 - Data Processing at Scale. Credits. 3 Recent Professors. Samira Ghayekhloo, Yuhan Sun, Jia Yu, Isaac Jones. Open Seat Checker. Get notified when CSE 511 has ...
I am Data Scientist at GoldSpot Discoveries Corp, former lead software engineer at Avestec Technologies Inc. I received my M.Sc. from Computer Science department at University of British Columbia (UBC) in 2019. My thesis focused on applying new machine learning and image processing techniques in geology and mineral exploration.
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UC San Diego Database Lab. The Database Lab at UC San Diego is one of the leading academic research groups in the field of data management, spanning the major themes of theory, systems, languages, interfaces, and applications, as well as intersections with other data-oriented fields. Data Augmentation with Atomic Templates for Spoken Language Understanding. In 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP 2019), Hong Kong, China, 2019, 3628–3634. PDF

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I received my Ph.D. from the Department of Computer Science at George Mason University in 2018. My advisor was Professor Songqing Chen. My research interests are multimedia systems and big data systems. I am actively looking for motivated students to join my research group . Feel free to contact me if your research interests are aligned with mine. I'm teaching COMP 150: Natural Language Processing at Tufts University Computer Science department. Research Interests Natural Language Processing (NLP), Automatic Knowledge Base Construction (AKBC), Information Extraction, Causal Reasoning, Question Answering, Machine Learning with applications to AKBC&NLP. Published in International Journal of Advanced Computer Science and Applications, 2018 Recommended citation: M. H. Alomari, O. Younis, and S. Hayajneh (2018). "A Predictive Model for Solar Photovoltaic Power using the Levenberg-Marquardt and Bayesian Regularization Algorithms and Real-Time Weather Data", International Journal of Advanced ...

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I did my PhD study in the School of Computer Science and Engineering, Nanyang Technological University from August 2010 to October 2014, under the supervision of Prof. Gao Cong. Prior to joining NTU, I was a scientific assistant in the Center for Data-Intensive Systems at Aalborg University from September 2008 to June 2010, under the ... Jedidiah McClurg. Computer Science Departmental Outstanding Research Award. 2017. Saeid Tizpaz Niari. Second prize, Microsoft Research Open Source Challenge. 2016. Open positions. We are looking for enthusiastic PhD students and postdocs to join CUPLV. Please send me an email if you are interested in research on program verification and program ...

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Oct 11, 2017 · ADAL.NET (Microsoft.IdentityModel.Clients.ActiveDirectory) is an authentication library which enables developers to acquire tokens from Azure AD and ADFS, to be used to access Microsoft APIs or applications registered with Azure Active Directory.

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‪Twitter / Imperial College London / University of Lugano‬ - ‪Cited by 17,940‬ - ‪geometric deep learning‬ - ‪graph representation learning‬ - ‪graph neural networks‬ - ‪shape analysis‬ - ‪geometry processing‬ You will write production-grade code and train Brain-Computer Interface models on large amounts of EEG data. Professional Requirements. 3+ years of programming experience, 2+ years in Python; Bachelor’s degree in Computer Science, Electrical Engineering, Applied Math, Computational Neuroscience or comparable discipline, Masters preferred. Dec 10, 2020 · Project page Paper Video Data Code on GitHub BibTex entry Neural Cages for Detail-Preserving 3D Deformations PUBLICATION CVPR 2020 (oral) / AUTHORS Wang Yifan , Noam Aigerman , Vladimir G. Kim , Siddhartha Chaudhuri , Olga Sorkine-Hornung

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Data Integration and Large-Scale Analysis WS2020/21 (VU, 706.520 Data Integration and Large-Scale Analysis) DIA is a 5 ECTS bachelor and master course, applicable to the bachelor programs computer science or software engineering and management, as well as the master catalog 'Data Science'. A professional programmer by trade, a Data Scientist by vocation, Benjamin's writing pursues a diverse range of subjects from Natural Language Processing, to Data Science with Python to analytics with Hadoop and Spark. Dr. Rebecca Bilbro is a data scientist, Python programmer, and author in Washington, DC.

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Hans Ulrich Simon Professor of Computer Science, ... Advances in neural information processing systems, 137-144, 2007. ... Scale-sensitive dimensions, uniform ... About me. I am a Research Staff Member at IBM Research - Almaden.My research interests are in the area of database systems and data analytics. In particular, my research focuses on query processing and optimizations, scalable data stream processing systems, and complex event processing systems.

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I'm looking for a method for scale and rotation invariant Template matching. I already tried some, but they didn't work so good for my examples or took for ever to execute . SIFT and SURF Feature detection failed totally. Giving people the power to share and connect requires constant innovation. At Facebook, research permeates everything we do. It’s more than a lab – it’s a way of doing things, and our teams of world-class scientists and engineers are up to the task.

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Management of Non-functional Attributes of Parallel Components. Procedia Computer Science 4 (2011): 461-470. [ICA3PP'2010] Qian Cao, Changjun Hu, Haohu He, Xiang Huang, and Shigang Li. Support for OpenMP tasks on cell architecture. In International Conference on Algorithms and Architectures for Parallel Processing, Workshop, pp. 308-317.

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Ph.D. in Computer Science, Department of Computer Science, The University of Georgia, 2010 - 2016. B.SC. in Applied Mathematics, The University of Kashan, Iran, 2001 - 2005