Computational learning theory - PowerPoint PPT Presentation


M.Tech. (Computational and Data Science)

Get all the information you need about the M.Tech. (Computational and Data Science) course structure, duration, core courses, soft core courses, dissertation, and electives.

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Universal Two-Qubit Computational Register for Trapped Ion Quantum Processors

Universal two-qubit computational register for trapped ion quantum processors, including state preparation, gates, and benchmarking. The experimental setup and results are discussed.

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Computational Physics (Lecture 18)

The basic structure of MPICH and its features in Computational Physics Lecture 18. Understand how MPI functions are used and linked with a static library provided by the software package. Explore how P4 offers functionality and supports parallel computer systems. Discover the concept of clusters in

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Cryptographic Reductions and Learning in Computational Complexity

This lecture explores the connection between computational complexity and cryptography, focusing on topics like pseudorandom functions, public-key cryptography, and learning from Gaussians. It delves into the implications of cryptographic reductions, lower bounds for learning MLPs, and the existence

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Understanding Signed Integers and Addition in Computational Systems

Dive into the world of signed integers, extensions, truncations, and addition in computer science with a focus on how negative values are represented and operated on. Explore concepts like sign-magnitude and two's complement representations, uncovering the intricacies of handling integers in computa

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OBPMark and OBPMark-ML: Computational Benchmarks for Space Applications

OBPMark and OBPMark-ML are computational benchmarks developed by ESA and BSC/UPC for on-board data processing and machine learning in space applications. These benchmarks aim to standardize performance comparison across different processing devices, identify key parameters, and provide recommendatio

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Computational thinking as 21st Century skill

Computational thinking is a critical skill for the digital age, involving problem-solving techniques that enable computers to process information effectively. It precedes programming and requires breaking down complex problems into manageable steps. Educators emphasize computational thinking exercis

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Computational Geometry.

Voronoi diagrams, a key concept in computational geometry, involve partitioning a space based on points sites. They have diverse applications like nearest neighbor queries and facility location. The diagrams consist of Voronoi cells, edges, and vertices, forming a connected graph. Properties include

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Understanding Social Learning Theory and the Power of Example

Social Learning Theory, introduced by Bandura, emphasizes learning through observation and modeling. It explores how individuals acquire behavioral dispositions, trial-and-error experiences, and the impact of stimuli in the environment. The theory focuses on the importance of attention, retention, a

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Master's Program in Computational Drug Discovery and Development - Fall 2024 Curriculum

This Master's program offers a comprehensive curriculum focusing on Artificial Intelligence, Computational Drug Discovery, and Development. With a blend of cutting-edge technologies and practical applications, students delve into techniques, AI/ML, big data mining, modeling, and more. Through intens

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Evolution of Mathematical Theories and Proof Systems

Development of mathematical theories such as model theory, proof theory, set theory, recursion theory, and computational complexity is discussed, starting from historical perspectives with Dedekind and Peano to Godel's theorems, recursion theory's golden age in the 1930s, and advancements in proof t

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Understanding Computational Linguistics and Natural Language Processing

Explore the fascinating fields of Computational Linguistics and Natural Language Processing (NLP), delving into their development, applications, and significance. Learn about the study of human languages in computational models, the importance of corpora in linguistic research, and the various types

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Understanding Forgetting: Theories and Influence on Memory Recall

Forgetting is a complex phenomenon influenced by theories such as Decay Theory, Interference Theory, and Motivated Forgetting. The Ebbinghaus forgetting curve highlights how memories fade over time. Decay Theory suggests memories decay over time, while Interference Theory explains how old and new me

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Psychological Theories of Criminality: Understanding the Roots

Psychological theories of criminality delve into the association between intelligence, personality, learning, and criminal behavior. Major theories include Psychodynamic Theory by Freud, Behavioral Theory by Bandura, and Cognitive Theory by Kohlberg. These theories explore how unconscious mental pro

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Understanding the Importance of Pattern Recognition in Computational Thinking

Pattern recognition is a vital skill in computational thinking, enabling the identification of similarities and differences between concepts and objects. By recognizing patterns, individuals can efficiently solve complex problems, create shortcuts, and avoid duplications in problem-solving processes

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Engaging Paper-Based Problem Solving for Computational Thinking Skills

Implementing paper-based problem-solving activities using puzzles, riddles, and pattern recognition can effectively introduce computational thinking without the need for complex technology or terminology. Through real-life scenarios like transporting a fox, chicken, and corn across a river or encodi

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Understanding Principles of Learning Theory and Behavioral Modification

Explore the principles of learning theory and its application in behavioral modification, highlighting concepts such as classical and operant conditioning. Learning, defined as a permanent change in behavior due to experience, is distinguished from performance. Discover how learning potential differ

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Insights on Computational Complexity Threshold Results

Exploring the challenges in proving major lower bounds for computational complexity, focusing on the Hardness Magnification and Minimum Circuit Size Problem (MCSP). Discusses the difficulties in proving weak and strong LBs, highlighting recent theorems and barriers that impact progress in the field.

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Understanding the Theory of Firms: Neoclassical vs. Modern Approaches

The theory of firms is explored through the Neoclassical and Modern perspectives. Neoclassical theory focuses on profit maximization, while Modern theory delves into managerial, principal-agent, and transaction cost theories. The discussion covers criticisms of Neoclassical theory and the essential

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Recent Advances in Computational Doppler Radar Data Modeling

Explore the latest developments in computational modeling of Doppler radar data, focusing on error estimation, dual vs. single pol radars comparison, uncertainty quantification, and methodology for analyzing Doppler radar predictions against gauge measurements. The study involves data from multiple

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Theories of Causation in Psychological and Social Sciences

Overview of theories of causation categorized into psychological, social psychological, and sociological perspectives. Psychological theories focus on instinctive, biological, and psychological qualities of abusers, including Attachment Theory, Psychodynamic Theory, Social Learning Theory, and Situa

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Understanding Political Theory through a Contextual Approach

Exploring G.H. Sabine's perspective on political theory through a contextual approach, emphasizing the importance of historical context and societal influences. Sabine argues that while political theory evolves with its contemporary politics, it should be analyzed within its specific time and social

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Understanding High Dynamic Range Sensors in Computational Photography

Dive into the world of High Dynamic Range (HDR) sensors in computational photography with topics covering sensor architectures, CMOS sensing techniques, dynamic range evaluation, and basic concepts related to image sensors and pixel integrators. Explore the importance of dynamic range in capturing a

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Computational Photography: Texture Synthesis and Hole-Filling Overview

Delve into the world of texture synthesis and hole-filling in computational photography, exploring the challenges, goals, and techniques involved in creating new textures and filling in image gaps. Learn about building probability distributions, modeling textures, and the intricacies of synthesizing

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Image-Based Lighting in Computational Photography

Explore the techniques and concepts of image-based lighting in computational photography through slides covering topics such as rendering objects in images, using environment maps and light probes, mirrored spheres, and dealing with light sources like the sun. Learn about capturing and utilizing lig

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Evolution of Light Theory: From Wave Theory to Quantum Theory

At the turn of the century, the discovery of the photoelectric effect challenged the wave theory of light, leading to the development of the quantum theory by Max Planck and Albert Einstein. This new theory introduced the concept of discrete energy units known as quanta, bridging the gap between wav

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Understanding Social Cognitive Theory: Insights from Albert Bandura

Social Cognitive Theory, developed by Albert Bandura, emphasizes learning through observation and modeling behaviors. The theory explores how individuals acquire new behaviors, thoughts, and attitudes by observing others. Bandura's famous Bobo doll experiment showcased how children imitated aggressi

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Dp-branes, NS5-branes, U-duality, and M-Theory Overview

Overview of Dp-branes, NS5-branes, and U-duality derived from nonabelian (2,0) theory with Lie 3-algebra. Introduction to M-theory, including M2-branes and M5-branes in the strong coupling limit. Discussion on BLG theory, Lorentzian Lie 3-algebra, and the ABJM theory for M2-branes.

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Innovative Learning Management System - LAMS at Belgrade Metropolitan University

Belgrade Metropolitan University (BMU) utilizes the Learning Activity Management System (LAMS) to enhance the learning process by integrating learning objects with various activities. This system allows for complex learning processes, mixing learning objects with LAMS activities effectively. The pro

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Exploring Complexity in Computational Theory

Dive into a world of computational complexity and theory with a focus on topics such as NP, P, PH, PSPACE, NL, L, random vs. deterministic algorithms, and the interplay of time and space complexity. Discover insights on lower bounds, randomness, expanders, noise removal, and the intriguing question

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Understanding Computational Complexity Through Statistical Physics

In the age of vast data growth, tackling complex computational problems is crucial. Statistical physics can provide insights into handling the new challenges arising from the exponential increase in data. As we delve into understanding the complexity of computational tasks, it becomes evident that e

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Introduction to Priority Search Trees in Computational Geometry

This lecture outlines the structure and query process of Priority Search Trees (PST) in computational geometry. It covers heap-based point queries, range trees for windowing queries, handling query ranges in 1D and 2D spaces, and using heaps to efficiently handle query ranges. The content discusses

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Understanding Time-Independent Perturbation Theory in Quantum Mechanics

Perturbation theory is a powerful tool in solving complex physical and mathematical problems approximately by adjusting solutions from a related problem with known solutions. This theory allows for more accurate approximate solutions by treating the difference as a small perturbation. An example inv

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Ethical Theories: Divine Command vs. Virtue Theory Explained

Divine Command Theory asserts that morality is derived from God's commands, contrasting with Virtue Theory which focuses on developing moral virtues to achieve human flourishing and excellence. Divine Command Theory relies on religious texts, while Virtue Theory emphasizes the cultivation of virtues

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Ladner's Theorem in Computational Complexity Theory

Ladner's Theorem is a significant result in computational complexity theory that deals with NP-intermediate problems, which are languages in NP neither in P nor NP-complete. The theorem states that if P is not equal to NP, then there must exist an NP-intermediate language. The proof involves a delic

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Understanding Fermi Liquid Theory in Interacting Fermion Systems

Fermi liquid theory, also known as Landau-Fermi liquid theory, is a theoretical model that describes the normal state of metals at low temperatures. Introduced by Landau and further developed by Abrikosov and Khalatnikov, this theory explains the similarities and differences between interacting ferm

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Advancing Computational Modeling for National Security and Climate Missions

Irina Tezaur leads the Quantitative Modeling & Analysis Department, focusing on computational modeling and simulation of complex multi-scale, multi-physics problems. Her work benefits DOE nuclear weapons, national security, and climate missions. By employing innovative techniques like model order re

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Understanding Decision Problems in Polynomial Time Complexity

Decision problems play a crucial role in computational complexity theory, especially in the context of P and NP classes. These problems involve questions with yes or no answers, where the input describes specific instances. By focusing on polynomial-time algorithms, we explore the distinction betwee

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Understanding Computational Biology: Proteins, DNA, RNA, Genetics, and Evolution

Computational Biology combines computational methods with molecular biology to solve biological problems. Explore topics like proteins, DNA, RNA, and genetics, learning about amino acids, nucleotides, and the genetic code. Understand the evolutionary processes of mutation and natural selection.

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Computational Learning Theory: An Overview

Computational Learning Theory explores inductive learning algorithms that generate hypotheses from training sets, emphasizing the uncertainty of generalization. The theory introduces probabilities to measure correctness and certainty, addressing challenges in learning hidden concepts. Through exampl

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