Alexandros biliris6/22/2023 The concurrency control problem in multidatabases: characteristics and solutions (hal 188 - 297)Īuthor: Sharad Mehrotra, Rajeev Rastogi, Yuri Breitbart, Henry F.Korth, Avi Silberschatz | Publisher: Proceedings of the 1992 acm sigmod international conference on management of data san diego,carlifonia june 2-5,1992 | Call Number: SEM - 359 | Edition: PERENCANAAN STRATEGIS SISTEM INFORMASI UNTUK MENDUKUNG STRATEGI BISNIS PADA BALAI BESAR PULP DAN KERTAS DI BANDUNG(47-52)Īuthor: NANANG SASONGKO TAUFAN HIDAYAT | Publisher: Prosiding seminar nasional aplikasi teknologi informasi 2008(SNATI 2008), Yogyakarta, 21 Juni 2008 | Call Number: SEM-309 | Edition: Simple rational guidance for chopping up transactions (hal 298 - 307 )Īuthor: Dennis Shasha, Eric Simon and Patrick Valduriez | Publisher: Proceedings of the 1992 acm sigmod international conference on management of data san diego,carlifonia june 2-5,1992 | Call Number: SEM - 359 | Edition: Performance evaluation of extended torage architectures for trnsaction processing (hal 308 - 320 )Īuthor: Erhard Rahm | Publisher: Proceedings of the 1992 acm sigmod international conference on management of data san diego,carlifonia june 2-5,1992 | Call Number: SEM - 359 | Edition: Algorithms will be implemented in either Matlab or Python.Indeks Artikel prosiding/Sem contains 4536 collection(s) Miscellaneous topics: design and analysis of data structures for fast Nearest Neighbor search such as Cover Trees and LSH. Topics in dimensionality reduction: linear techniques such as PCA, ICA, Factor Analysis, Random Projections, non-linear techniques such as LLE, IsoMap, Laplacian Eigenmaps, tSNE, and study of embeddings of general metric spaces, what sorts of theoretical guarantees can one provide about such techniques. Topics in clustering: k-means clustering, hierarchical clustering, spectral clustering, clustering with various forms of feedback, good initialization techniques and convergence analysis of various clustering procedures. Ability to program in a high-level language, and familiarity with basic algorithm design and coding principles.Ĭore topics from unsupervised learning such as clustering, dimensionality reduction and density estimation will be studied in detail. Background in probability and statistics, linear algebra, and multivariate calculus. Prerequisites: Machine Learning (COMS W4771). The field explores techniques for assessing current information practices, determining the information needs of health care providers and patients, developing interventions using computer technology, and evaluating the impact of those interventions.ĬOMS W4773 Machine Learning Theory. Biomedical Informatics studies the organization of medical information, the effective management of information using computer technology, and the impact of such technology on medical research, education, and patient care. Use of computers and information in health care and the biomedical sciences, covering specific applications and general methods, current issues, capabilities and limitations of biomedical informatics. Undergraduates in their senior or junior years may take this course only if they have adequate background in mathematics and receive the instructor's permission.Īn overview of the field of biomedical informatics, combining perspectives from medicine, computer science and social science. Prerequisites: Experience with computers and a passing familiarity with medicine and biology. All the while, we continue to develop our fluency in live coding by putting new topics to practice.ĬOMS W4560 Introduction to Computer Applications in Health Care and Biomedicine. For the third module, we turn our focus to automated composition and analysis, addressing challenges in music information retrieval, generative art, and autonomous improvisation systems. In the space of live coding, we examine various programming language designs to understand how various domain specific languages (DSLs) support live coding. After covering some core DSP techniques, we put these concepts into performative practice by exploring “live coding”. We then move through various synthesis techniques including the additive, subtractive, frequency modulation (FM), and amplitude modulation (AM) synthesis. We start with the fundamentals of sound in the digital domain, covering issues of representation and audio synthesis. In this course, we explore the variety of roles that computation can play in the analysis, creation, and performance of music.
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