| source Yale (X) |
level |
department Applied Mathematics (X) |
MWF 1.30-2.20 Fall 2009 Final exam scheduled (Group 36) 12/14/2009 M 2.00 Skills QR Methods of quantitative inference and modeling are introduced via applications from a variety of different fields. Possible topics include data encryption, codes, scaling phenomena, traffic flow, warfare, and population growth. Some use of computing software such as Mathematica or MATLAB.
Score: 10.705657 Details | Listing | Web page
MWF 10.30-11.20 Fall 2009 Final exam scheduled (Group 69) 12/16/2009 W 9.00 Matrix representation of linear equations. Gauss elimination. Vector spaces. Linear independence, basis, and dimension. Orthogonality, projection, least squares approximation; orthogonalization and orthogonal bases. Extension to function spaces. Determinants. Eigenvalues and eigenvectors. Diagonalization. Difference equation and matrix differential equations. Symmetric and Hermitian matrices. Orthogonal and unitary transformations; similarity transformations.
Score: 10.705657 Details | Listing | Web page
TTh 1.00-2.15 Fall 2009 Final exam scheduled (Group 26) 12/15/2009 T 2.00 Skills QR Resource allocation problems solved by linear programming and its generalizations: the simplex method, duality, the Karush-Kuhn-Tucker conditions for nonlinear programs, economic equilibria, and selected applications.
Score: 10.705657 Details | Listing | Web page
TTh 11.35-12.50 Fall 2009 Final exam scheduled (Group 24) 12/15/2009 T 9.00 Skills QR Basic concepts and results in discrete mathematics: graphs, trees, connectivity, Ramsey theorem, enumeration, binomial coefficients, Stirling numbers. Properties of finite set systems.
Score: 10.705657 Details | Listing | Web page
MW 1.00-2.15 Fall 2009 Final exam scheduled (Group 36) 12/14/2009 M 2.00 Skills QR Permission of instructor required Introduction to finite-dimensional, continuous, and discrete-time linear dynamical systems. Exploration of the basic properties and mathematical structure of the linear systems used for modeling dynamical processes in robotics, signal and image processing, economics, statistics, environmental and biomedical engineering, and control theory.
Score: 10.705657 Details | Listing | Web page
MW 2.30-3.45 Fall 2009 No regular final examination Skills QR Through analysis of data sets using the R statistical computing language, study of a selection of statistical topics such as linear and nonlinear models, maximum likelihood, resampling methods, curve estimation, model selection, classification, and clustering. Weekly sessions in the Statistical Computing laboratory.
Score: 10.705657 Details | Listing | Web page
MW 2.30-3.45 Fall 2009 Final exam scheduled (Group 37) 12/18/2009 F 2.00 Skills QR Permission of instructor required Fundamental theory and algorithms of optimization, emphasizing convex optimization. The geometry of convex sets, basic convex analysis, the principle of optimality, duality. Numerical algorithms: steepest descent, Newton's method, interior point methods, dynamic programming, unimodal search. Applications from engineering and the sciences.
Score: 10.705657 Details | Listing | Web page
1 HTBA Fall 2009 No regular final examination Permission of instructor required Individual study for qualified students who wish to investigate an area of applied mathematics not covered in regular courses. A student must be sponsored by a faculty member who sets the requirements and meets regularly with the student. Requires a written plan of study approved by the faculty adviser and the director of undergraduate studies.
Score: 10.705657 Details | Listing | Web page
W 3.30-5.20 Fall 2009 No regular final examination Permission of instructor required Under the supervision of a member of the faculty, each student works on an independent project. Students participate in seminar meetings at which they speak on the progress of their projects. Some meetings may be devoted to talks by visiting faculty members or applied mathematicians.
Score: 10.705657 Details | Listing | Web page
1 HTBA Fall 2009 No regular final examination Permission of instructor required Individual research. Requires a faculty supervisor and the permission of the director of undergraduate studies. The student must submit a written report about the results of the project.
Score: 10.705657 Details | Listing | Web page
AMTH 561 01 (10241) /CPSC662 WF 2.30-3.45 Fall 2009 An applied approach to spectral graph theory. The combinatorial meaning of the eigenvalues and eigenvectors of matrices associated with graphs. Applications to optimization, numerical linear algebra, error-correcting codes, and testing graph isomorphism.
Score: 10.705657 Details | Listing | Web page
AMTH 605 01 (10242) /ENAS503/STAT667 TTh 1.00-2.15 Fall 2009 This course examines probabilistic and computational methods for the statistical modeling of complex data. The emphasis is on the unifying framework provided by graph models: Markov random fields, Bayesian networks, and factor graphs. Algorithms: filtering, smoothing, belief-propagation, sum-product, and junction tree. Variational techniques: mean-field and convex relaxations. Markov processes on graphs: MCMC, factored HMMs, and Glauber dynamics. Some statistical physics techniques: cavity and replica methods. Applications to error-correcting codes, computer vision, bio-informatics, and combinatorial optimization.
Score: 10.705657 Details | Listing | Web page
AMTH 664 01 (10245) HTBA Fall 2009 An overview of basic topics in computational biology, spanning scales from molecules to cells to networks. How cells process information (cell biology); how neurons sense the world and make decisions (neurobiology); and how genes control form (evolutionary biology). Prerequisite: MATH 120a or b or equivalent.
Score: 10.705657 Details | Listing | Web page
AMTH 666 01 (10246) /ASTR666/G&G666 TTh 2.30-3.45 Fall 2009 Classical thermodynamics is derived from statistical thermodynamics. We then develop kinetics, transport theory, and reciprocity from the linear thermodynamics of irreversible processes. Emphasis is placed on phase transitions, including novel states of matter, nucleation theory, and the thermodynamics of atmospheres. We explore phenomena that are of direct relevance to problems in astrophysical settings, atmospheres, oceans, and the Earth's interior. No quantum mechanics is necessary as a prerequisite.
Score: 10.705657 Details | Listing | Web page