Delve into computability theory, focusing on what is computable and the limits of computation. Explore concepts like Rice's Theorem, the Halting Problem, and classes of expressiveness in computability theory, such as combinational logic, finite-state machines, pushdown automata, and Turing machines.

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Characterizing Distributed Systems: Multiple autonomous computers with CPUs, memory, storage, and I/O paths, interconnected geographically, shared state, global invariants. Classifying Distributed Systems: Based on synchrony, communication medium, fault models like crash and Byzantine failures. Comp

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Computation of Machine Hour Rate (MHR) involves determining the overhead cost of running a machine for one hour. The process includes dividing overheads into fixed and variable categories, calculating fixed overhead hourly rates, computing variable overhead rates, and summing up both for the final M

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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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Delve into the world of numerical methods through the guidance of Dr. M. Mohamed Surputheen. Explore topics such as solving algebraic and transcendental equations, simultaneous linear algebraic equations, interpolation, numerical integration, and solving ordinary differential equations. Learn about

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Learn about income computation of trusts using ITR-5 vs. ITR-7, types of institutions, components of income, application of income, and important guidelines including amendments by FA2022 for charitable and religious trusts.

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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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Utilizing evidence-based methods, this study explores incorporating computation in physics courses, focusing on instructional design, student knowledge states, and preparation for future learning. It discusses common conceptual difficulties in quantum mechanics and proposes cognitive theory-based st

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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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In this content, we dive into the fundamentals of sequence alignment, Opt score computation, reconstructing alignments, local alignments, affine gap costs, space-saving measures, and scoring matrices for DNA and protein sequences. We explore the Smith-Waterman algorithm (SW) for local sequence align

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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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PIM technology aims to enhance performance by moving computation closer to memory, improving bandwidth, latency, and energy efficiency. Despite initial setbacks, new strategies focus on cost-effectiveness, programming models, and overcoming implementation challenges. A new direction proposes intuiti

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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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Autonomous Agents-based Mobile-Cloud Computing (MCC) refers to moving computing tasks to powerful centralized platforms in the cloud, offering advantages like extending battery life and dynamic resource provisioning. However, an inflexible split of computation between mobile and cloud platforms lead

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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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Improving I/O performance and efficiency on Simultaneous Multi-Threading (SMT) processors in virtualized clouds is crucial for maximizing system throughput and resource utilization. The vSMT-IO approach focuses on efficiently scheduling I/O workloads on SMT CPUs by making them "dormant" on hardware

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Fully Homomorphic Encryption (FHE) allows evaluation of unbounded-depth circuits without being limited by specific parameters. Bootstrapping is a critical technique to achieve full homomorphism by refreshing ciphertexts, enabling decryption functionalities within the encryption scheme. This process

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Homomorphic encryption allows computation on encrypted data, enabling privacy in outsourced computing services and applications like spam filters for encrypted mail. The Ring Learning With Errors (RLWE) scheme and its properties are discussed, along with symmetric encryption from RLWE and fully homo

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Explore the innovative approaches to Multi-Party Computation (MPC) such as MPC via Fully Homomorphic Encryption (FHE) and Multi-Key FHE. The focus is on minimizing round complexity and achieving secure distributed computations. Learn about key concepts, protocols, and advancements in the realm of MP

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Balanced graph edge partitioning is a crucial problem in graph computation, machine learning, and graph databases. It involves partitioning a graph's vertices or edges into balanced components while minimizing cut costs. This process is essential for various real-world applications such as iterative

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Garbled RAM, a concept based on garbled circuits, allows for secure two-party computation with implications for communication and computational complexities. The progression from basic to more ambitious scenarios in Garbled RAM models and the landscape of utilizing OWFs in a black-box manner for imp

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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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Exploring the concept of undecidability in computing, we delve into the question of whether there are tasks that cannot be computed. The journey leads us to the theorem that the language ATM, defined as containing Turing Machine descriptions accepting input strings, is undecidable, showcasing the fu

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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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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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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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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 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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The Cognitive Computation Group Curator provides a range of NLP tools for tasks such as Tokenization, Part-Of-Speech Tagging, Named Entity Recognition, and more. Users can access these tools in various programming languages like Python, Java, and Perl, with a focus on creating efficient NLP pipeline

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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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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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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 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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Introducing a powerful form of computation that includes error correction and high precision in FPGA, with modules for multiplication, accumulation, and conversion from binary to fixed-point RNS format. The advancements provide carry-free operations, efficient space allocation, and accurate results

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