Explore Microsoft's innovative approach to query optimization in production environments, addressing challenges with general-purpose optimization and introducing specialized cloud-based optimizers. Learn about the implementation details, experiments conducted, and the solution proposed. Discover how

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This lecture outline delves into the concepts of evolution, unity, and diversity of organisms on Earth, covering topics such as fossils, Lamarck and Darwin's theories, adaptation, natural selection, artificial selection, Carolus Linnaeus' systematics, plant evolution, and the demonstration of evolut

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Differences in functional and structural constraints across sites lead to varying rates of evolution in molecular sequences. Understanding the complexities of site-specific rates, among-site rate variation, site-specific rates models, invariable sites model, and continuous methods is crucial for acc

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Optimization in process engineering involves obtaining the best possible solution for a given process by minimizing or maximizing a specific performance criterion while considering various constraints. This process is crucial for achieving improved yields, reducing pollutants, energy consumption, an

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Swarm Intelligence (SI) is an artificial intelligence technique inspired by collective behavior in nature, where decentralized agents interact to achieve goals. Swarms are loosely structured groups of interacting agents that exhibit collective behavior. Examples include ant colonies, flocking birds,

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Peripatus, known as claw bearers, exhibits characteristics of both annelids and arthropods, making it an intriguing species in the study of evolutionary biology. Considered as an intermediate link between these two phyla, Peripatus raises questions about its classification and evolutionary history.

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Phylogeny is the study of evolutionary relationships among organisms, depicted in phylogenetic trees based on shared characteristics. This overview delves into terms like homology, analogy, monophyly, and co-evolution in angiosperms with an emphasis on taxonomy, systematics, and the evolutionary his

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Cladograms are used in cladistics to illustrate evolutionary relationships between organisms based on shared ancestral and derived characters. They are created by grouping species by common descent, forming clades that include an ancestral species and all its descendants. Valid clades are monophylet

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Exploring the forces behind evolutionary change, this content delves into natural selection, genetic drift, and gene flow. Examples such as the bottleneck effect, founder effect, and Amish population polydactylism are presented to illustrate how these mechanisms shape genetic diversity. The impact o

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The DNN Inference Optimization Challenge, organized by Liya Yuan from ZTE, focuses on optimizing deep neural network (DNN) models for efficient inference on-device, at the edge, and in the cloud. The challenge addresses the need for high accuracy while minimizing data center consumption and inferenc

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Basidiomycota, a successful fungal group with 30,000 known species, predominantly exhibits filamentous vegetative growth while also producing yeast forms. The multi-layered cell wall and regularly septate hyphae with dikaryotic mycelium are key characteristics. Recent experimentation on Schizophyllu

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Explore the modes of speciation and causes of extinction in the evolutionary process. Learn how species evolve to become distinct through geographic isolation and reduced gene flow. Understand the implications of extinction and its impact on biodiversity. Images and descriptions provided offer insig

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Taxonomy, derived from Greek roots, encompasses the science of classifying organisms and understanding their variations, evolutionary relationships, and naming conventions. It involves description, identification, classification, and nomenclature of both living and extinct organisms. The practices o

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This seminar at the University of Zurich, led by Prof. Sebastian Schnettler, delves into the realm of evolutionary sociology, examining the impact of genetics, hormones, and social processes on human behavior. The course integrates biology and sociology, offering a variety of approaches to understan

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Monera, the simplest yet diverse kingdom, is divided into Archaebacteria and Eubacteria. Archaebacteria are ancient, thriving in extreme conditions, while Eubacteria encompass true bacteria with various metabolic capabilities. Actinomycetes, unique filamentous bacteria, play vital roles in soil ecos

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The production order highlights the essential role of genomic variation as fuel for natural selection, driving evolutionary adaptation. The Cambrian Explosion timeframe reveals a rapid increase in evolutionary adaptation, showcasing the appearance of diverse animal phyla over a relatively short peri

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Explore the complexities of multiple objective linear programming, decision-making with multiple objectives, goal programming, and evolutionary multi-objective optimization. Discover the trade-offs and conflicts between various objectives in optimization problems.

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Discrete Optimization is a field of applied mathematics that uses techniques from combinatorics, graph theory, linear programming, and algorithms to solve optimization problems over discrete structures. This involves creating mathematical models, defining objective functions, decision variables, and

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This study delves into the generalization of Empirical Risk Minimization (ERM) in stochastic convex optimization, focusing on minimizing true objective functions while considering generalization errors. It explores the application of ERM in machine learning and statistics, particularly in supervised

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Explore the world of optimization through convex and general problems, understanding the concepts, constraints, and the difference between convex and non-convex optimization. Discover the significance of local and global optima in solving complex optimization challenges.

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Explore the basic components of optimization problems, such as objective functions, constraints, and global vs. local optima. Learn about single vs. multiple objective functions and constrained vs. unconstrained optimization problems. Dive into the statement of optimization problems and the concept

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Study on computing triplet and quartet distances in evolutionary trees, comparing rooted vs. unrooted, binary vs. arbitrary degree trees. Discusses algorithms, experimental results, and evolutionary tree construction methods. Includes analysis on cultural phylogenetics and evolutionary tree comparis

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Recent research highlights advancements in solving sampling problems in convex optimization, exemplified by works by Yin Tat Lee and Santosh Vempala. The complexity of convex problems, such as the Minimum Cost Flow Problem and Submodular Minimization, are being unraveled through innovative formulas

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Scientists use classification to group organisms logically, making it easier to study life's diversity. Taxonomy assigns universally accepted names to organisms using binomial nomenclature. Carolus Linnaeus developed this system, organizing organisms into species, genus, family, order, class, phylum

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Meet the evolutionary pioneers - Mary Anning, Charles Darwin, and Alfred Russel Wallace, who played crucial roles in the development of evolutionary theory. Learn about their groundbreaking discoveries, challenges faced, and lasting impact on the scientific community.

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Dive into the world of evolutionary trees and family lineages through captivating visuals and informative illustrations. Explore the relationships between species, understand genetic connections, and discover how traits evolve and spread through generations. From evolutionary history to family trees

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This piece discusses approximation algorithms for stochastic optimization problems, focusing on modeling uncertainty in inputs, adapting to stochastic predictions, and exploring different optimization themes. It covers topics such as weakening the adversary in online stochastic optimization, two-sta

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Evolutionary algorithms, particularly genetic algorithms, simulate natural evolution to optimize parameters and discover new solutions. By creating genomes representing potential solutions and using genetic operators like mutation and crossover, these algorithms populate a search space, conduct loca

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Explore the world of evolutionary computation and genetic algorithms through a presentation outlining the concepts of genetic algorithms, parallel genetic algorithms, genetic programming, evolution strategies, classifier systems, and evolution programming. Delve into scenarios in the forest where gi

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This presentation compares three evolutionary parameters (dN, dS, dN/dS) between giraffe and okapi in a set of vision genes using the free-ratio model of the PAML program. The images illustrate the differences in nonsynonymous and synonymous substitutions, as well as the ratio of nonsynonymous to sy

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Delve into the complexities of human aggression, questioning whether it is inherent or a learned behavior. Explore evolutionary theories and biological perspectives on the causes of aggression, examining how factors such as genetics, brain structures, hormones, and environmental pressures may influe

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Exploring evolutionary theories such as Sexual Selection Theory and Gene Selection Theory sheds light on how characteristics evolve for mating advantage. Insights into intersexual and intrasexual competition offer a deeper understanding of mate selection preferences. Gene selection mechanisms influe

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Delve into the fascinating world of human origins, examining hominid fossils, anatomical traits, and evolutionary evidence. Learn about early species like Ardipithecus ramidus, differentiate African apes from modern humans, and analyze the genetic lineage supporting human evolution. Explore tables,

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Dichotomous keys are utilized to classify different organisms based on their physical characteristics, while cladograms depict evolutionary relationships. Derived traits play a crucial role in understanding evolutionary history, indicating features present in later organisms but not earlier ones. Pr

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Real-world design problems often require multi-objective optimization, and the Flower Pollination Algorithm (FPA) developed by Xin-She Yang in 2012 mimics the pollination process of flowering plants to efficiently solve such optimization tasks. FPA has shown promising results in extending to multi-o

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This research presents a hybrid optimization heuristic approach for efficient instruction scheduling in programmable accelerator codesign. It discusses Google's TPU architecture, problem-solving strategies, and computation graph mapping, routing, and timing optimizations. The technique overview high

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This presentation discusses the application of machine learning for optimizing EBIS beam intensity and RHIC luminosity. It covers topics such as motivation, EBIS beam intensity optimization, luminosity optimization, and outlines the plan and summary of the project. Collaborators from MSU, LBNL, and

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Bayesian optimization is being used at LCLS to tune the Free Electron Laser (FEL) pulse energy efficiently. The current approach involves a tradeoff between human optimization and numerical optimization methods, with Gaussian processes providing a probabilistic model for tuning strategies. Prior mea

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Explore the significance of phylogenomics in predicting gene functions and establishing evolutionary relationships using genome-scale data. Learn about the challenges of using single genes or a few genes in phylogenetic analysis, the importance of analyzing multilocus data, and the need for multiple

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The evolution of metalearning in the machine learning community is traced from the initial workshop in 1998 to recent developments in hyper-parameter optimization. Challenges in classifier selection and the validity of hyper-parameter optimization claims are discussed, urging the exploration of spec

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