This course at National Taipei University delves into fundamental concepts, research issues, and practical applications of Big Data Analysis. Taught by Dr. Min-Yuh Day, the syllabus covers topics such as AI, machine learning, deep learning, and industry practices related to big data analysis. Studen

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Over the past two decades, there has been a significant proliferation of big data, leading to the emergence of new challenges and opportunities in economic policy formulation. The use of big data, with its three defining characteristics (volume, velocity, and variety), poses questions about the futu

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Data migration tools are indispensable for organizations looking to transform their big data into actionable insights. Ask On Data exemplifies how these tools can streamline the migration process, ensuring data integrity, scalability, and security. By leveraging Ask On Data, organizations can achiev

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Explore the improved black-box constructions of composable secure computation, focusing on definitions, objectives, and the formalization basics of multiparty computation (MPC). Learn about the motivating security aspects in MPC and the real/ideal paradigm. Discover how MPC security involves compari

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Explore the automation of efficient RAM-model secure computation techniques, including examples such as secure binary search. Discover how traditional solutions using circuit abstractions can be improved for sub-linear time computation through methods like Oblivious RAM. Learn about techniques such

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This report discusses the use of Secure Multiparty Computation (SMC) to enable sharing of sensitive Department of Education data across organizational boundaries. The application of SMC allows for joint computation while keeping individual data encrypted, ensuring privacy and security within the Nat

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Delve into the realm of secure multiparty computation under 1-bit leakage, exploring the intersection of DP algorithms, MPC, and the utilization of leakage for enhanced performance. Discover the overhead implications of achieving active security, as well as the evolution of secure computation protoc

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Secure multiparty computation (SMC) enables parties with private inputs to compute joint functions without revealing individual data, ensuring privacy and correctness. This involves computations on encrypted data using techniques like homomorphic encryption for scenarios like e-voting. SMC serves as

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The research paper discusses COMET, a system for transparently offloading computation from mobile devices to network resources to improve performance. It outlines the goals of COMET, its design, and evaluation, focusing on distributed shared memory and bridging computation disparity through offloadi

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Exploring actively secure arithmetic computation and VOLE with constant computational overhead at Tel Aviv University. Understanding how functions are represented in secure computation using arithmetic circuits over boolean circuits. Efficiently evaluating arithmetic circuits over large finite field

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Harnessing the power of big data in astronomy, this presentation by Curt Dodds from the Institute for Astronomy at the University of Hawaii, Manoa, delves into the utilization of national cyberinfrastructure to advance artificial intelligence access and foster innovation in the field. The discussion

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Explore the realm of efficient random access in multi-party computation through the reevaluation of classic schemes and the introduction of new approaches. Discover the potential of ORAM in improving performance and reducing costs in various computational tasks, such as secure multi-party computatio

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Explore the intersection of big data and privacy through the insights of Bart van der Sloot. Delve into current privacy issues, the application of big data, legal frameworks, recent developments, and the challenges between big data and privacy protection. Gain knowledge from interactive debates, stu

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This research project led by Prof. Kazuo Ishii aims to develop a Big Data mining method and optimized algorithms for genomic Big Data, specifically targeting three major mental disorders including depression. The research process involves data analytics, mathematical modeling, and data processing te

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Welcome to Secure Computation Lecture 1 by Arpita Patra. The course covers evaluation policies, projects, and references in the realm of secure computation. The content delves into the significance of information security across various sectors, emphasizing the importance of safeguarding sensitive d

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The world has evolved into a data-centric landscape where managing massive amounts of data requires the convergence of big data, big knowledge, and big crowd technologies. This transformation necessitates the utilization of domain knowledge, building knowledge bases, and integrating human input thro

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In today's lecture of "Foundations of Cryptography," the focus is on secure two-party and multi-party computation, emphasizing semi-honest security where Alice and Bob must compute without revealing more than necessary. Concepts such as real-world vs. ideal-world scenarios, the existence of PPT simu

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The research focuses on achieving perfectly secure multiparty computation (MPC) with linear communication and constant expected time. It explores efficient approaches using a broadcast-hybrid model and P2P communication, aiming to balance speed and efficiency in MPC. The study highlights the importa

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Big data presents both risks and opportunities for development initiatives, with the potential to enhance policy-making processes. While big data can improve the efficiency of public policy and administration, concerns arise regarding data accuracy, inclusivity, and transparency. Upholding privacy p

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Big data involves analyzing and extracting information from large and complex datasets that traditional software cannot handle. AI algorithms play a crucial role in processing big data to find patterns that humans may overlook. Ethical considerations arise in defining what is "interesting" in the da

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Exploring the intersection of secure computation and data mining, this content uncovers key challenges such as improving algorithms, converting programs for secure computation, and addressing parallelizability issues. It highlights the importance of cryptography in ensuring data privacy and presents

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Covert computation aims to conceal the fact that computation is occurring and hide engagement in certain tasks like secure computation, authenticated key exchange, and more. By making messages indistinguishable and utilizing steganographic channels, it becomes possible to keep the activities covert

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Exploring fundamental challenges in computation within the big data era, this content delves into the complexities of handling social media data, emphasizing the importance of scalability, data relevancy, quality assurance, and data integration. Presented during a panel discussion at Arizona State U

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Turing Machines are fundamental in the theory of computation, capable of recognizing all computable languages. They consist of a Finite State Machine combined with an infinite tape. The tape is initialized with input on the left end, and a TM's computation can either halt by entering special accept

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Practical overview of GST computation for real estate transactions in Bangalore, with details on old rates with ITC and new rate regime effective from April 1, 2019. The content discusses different transactions, conditions for new rates without ITC, and provides insights on the 80:20 computation met

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Fides presents a system for verifiable computation using smart contracts, focusing on blockchain basics, Ethereum, smart contracts, and outsourcing computation. It explores key components of blockchain, Ethereum's decentralized computing platform, properties of smart contracts, and the concept of ve

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Big data refers to vast and complex data sets difficult to process with traditional tools. Cloud computing tools like Hadoop and Spark enable the handling of big data. Types of big data include structured, unstructured, and semi-structured data. The evolution of technology, IoT devices, social media

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This paper revisits the concept of secure computation with minimal interaction, focusing on the challenges and possibilities of achieving secure multiparty computation in 2 rounds. Specifically exploring scenarios with 3 and 4 parties, the study delves into the reasons for choosing n=3, n=4, and t=1

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The EAA 2016 Symposium focused on the impact of big data in accounting and auditing, featuring presentations on using data analytics to enhance audit quality, the influence of big data on management accounting research and the accounting profession. Speakers highlighted the importance of dealing wit

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The Income-tax Act, 1961 introduced Income Computation and Disclosure Standards (ICDS) to be followed by certain assesses for computation of income. ICDS applies to taxpayers using the mercantile system of accounting from the Assessment Year 2016-17 onwards. Non-compliance with ICDS can lead to Best

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A data ecosystem encompasses infrastructure, analytics, and data analysis, fostering partnerships and coordination to leverage the power of data. This ecosystem, driven by Big Data technologies and deep analytical talent, aims to address complex business challenges and drive innovation. The integrat

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Mega-Modeling is a comprehensive approach that encompasses model construction, evaluation, composition, evolution, and search to address challenges in various areas such as social and economic resilience, health, transportation, and energy management. The pillars of Mega-Modeling include Model-Drive

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This summarized content discusses the concept of blackbox verifiable computation, focusing on the challenges faced by clients and servers, the role of helper oracles, positive results utilizing homomorphic encryption, and background information on Random Self Reducible (RSR) functions. The protocol

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Discussing the regulatory perspective on commercial versus humanitarian and development applications of big data, this conversation with regulators highlights the differences and similarities in utilizing data for various sectors. Emphasizing the importance of trust, confidentiality, and data securi

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Matrix multiplication is a fundamental operation with diverse applications across scientific research. Parallel computation for matrix multiplication involves distributing the computational workload over multiple processors, improving efficiency. Different algorithms have been developed for multiply

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Revealing the intricacies of parallel query processing on big data, this content explores various computation models such as MapReduce, MUD, and MRC. It delves into the MPC model in detail, showcasing the tradeoffs between space exponent and computation rounds. The study uncovers lower bounds on spa

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Explore the intersection of big data and historiography through insightful essays on the significance of big data, its historical prelude, current usage, and the evolving understanding of the self in history. Delve into discussions on the purpose, power, and implications of big data in shaping histo

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This content delves into the preprocessing, computing, post-processing, and analysis of raw XML data for graph-based algorithms. It covers topics such as data ETL, graph analytics, PageRank computation, and identifying top users. Various tools and frameworks like GraphX, Spark, Giraph, and GraphLab

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Explore the utilization of big data in official transport statistics, including real-time shipping data for port visits and traffic flow analysis. Discover the motivation, objectives, and benefits of incorporating big data in generating efficient and timely official statistics. Learn about the role

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Explore cutting-edge methods in Multi-Party Computation (MPC), including leveraging Fully Homomorphic Encryption (FHE) for minimal round complexity, constructing MPC directly via FHE techniques, and simplifying multi-key FHE constructions for efficient decryption. Learn about key concepts such as di

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