Courses tagged with "Graduate" (1105)
This course is organized around algorithmic issues that arise in machine learning. Modern machine learning systems are often built on top of algorithms that do not have provable guarantees, and it is the subject of debate when and why they work. In this class, we focus on designing algorithms whose performance we can rigorously analyze for fundamental machine learning problems.
6.890 Algorithmic Lower Bounds: Fun with Hardness Proofs is a class taking a practical approach to proving problems can't be solved efficiently (in polynomial time and assuming standard complexity-theoretic assumptions like P ≠ NP). The class focuses on reductions and techniques for proving problems are computationally hard for a variety of complexity classes. Along the way, the class will create many interesting gadgets, learn many hardness proof styles, explore the connection between games and computation, survey several important problems and complexity classes, and crush hopes and dreams (for fast optimal solutions).
Animation is a compelling and effective form of expression; it engages viewers and makes difficult concepts easier to grasp. Today's animation industry creates films, special effects, and games with stunning visual detail and quality. This graduate class will investigate the algorithms that make these animations possible: keyframing, inverse kinematics, physical simulation, optimization, optimal control, motion capture, and data-driven methods. Our study will also reveal the shortcomings of these sophisticated tools. The students will propose improvements and explore new methods for computer animation in semester-long research projects. The course should appeal to both students with general interest in computer graphics and students interested in new applications of machine learning, robotics, biomechanics, physics, applied mathematics and scientific computing.
This is a graduate-level introduction to the principles of statistical inference with probabilistic models defined using graphical representations. The material in this course constitutes a common foundation for work in machine learning, signal processing, artificial intelligence, computer vision, control, and communication. Ultimately, the subject is about teaching you contemporary approaches to, and perspectives on, problems of statistical inference.
This course examines the causes and consequences of American foreign policy since 1898. Course readings cover both substantive and methods topics. Four substantive topics are covered:
- major theories of American foreign policy;
- major episodes in the history of American foreign policy and historical/interpretive controversies about them;
- the evaluation of major past American foreign policies--were their results good or bad? and
- current policy controversies, including means of evaluating proposed policies.
Three methods topics are covered:
- basic social scientific inference--what are theories? what are good theories? how should theories be framed and tested?
- historical investigative methodology, including archival research, and, most importantly,
- case study methodology.
Historical episodes covered in the course are used as raw material for case studies, asking "if these episodes were the subject of case studies, how should those studies be performed, and what could be learned from them?"
This course surveys American political thought from the colonial era to the present. Required readings are drawn mainly from primary sources, including writings of politicians, activists, and theorists. Topics include the relationship between religion and politics, rights, federalism, national identity, republicanism versus liberalism, the relationship of subordinated groups to mainstream political discourse, and the role of ideas in politics. We will analyze the simultaneous radicalism and weakness of American liberalism, how the revolutionary ideas of freedom and equality run up against persistent patterns of inequality. Graduate students are expected to pursue the subject in greater depth through suggested reading and individual research.
The television landscape has changed drastically in the past few years; nowhere is this more prevalent than in the American daytime serial drama, one of the oldest forms of television content. This class examines the history of these "soap operas" and their audiences by focusing on the production, consumption, and media texts of soaps. The class will include discussions of what makes soap operas a unique form, the history of the genre, current experimentation with transmedia storytelling, the online fan community, and comparisons between daytime dramas and primetime serials from 24 to Friday Night Lights, through a study of Procter & Gamble's As the World Turns.
Intelligent Transportation Systems (ITS) represent a major transition in transportation on many dimensions. This course considers ITS as a lens through which one can view many transportation and societal issues. ITS is an international program intended to improve the effectiveness and efficiency of surface transportation systems through advanced technologies in information systems, communications, and sensors. In the United States, ITS represents the major post-Interstate-era program for advancing surface transportation in highways and public transportation, and is potentially comparable to the air traffic control system in impact. The readings for the class come primarily from the instructor's own text: Sussman, Joseph. Perspectives on Intelligent Transportation Systems (ITS). New York, NY: Springer, 2005. ISBN: 0387232575.
This course is a comprehensive introduction to control system synthesis in which the digital computer plays a major role, reinforced with hands-on laboratory experience. The course covers elements of real-time computer architecture; input-output interfaces and data converters; analysis and synthesis of sampled-data control systems using classical and modern (state-space) methods; analysis of trade-offs in control algorithms for computation speed and quantization effects. Laboratory projects emphasize practical digital servo interfacing and implementation problems with timing, noise, and nonlinear devices.
6.374 examines the device and circuit level optimization of digital building blocks. Topics covered include: MOS device models including Deep Sub-Micron effects; circuit design styles for logic, arithmetic and sequential blocks; estimation and minimization of energy consumption; interconnect models and parasitics; device sizing and logical effort; timing issues (clock skew and jitter) and active clock distribution techniques; memory architectures, circuits (sense amplifiers) and devices; testing of integrated circuits. The course employs extensive use of circuit layout and SPICE in design projects and software labs.
This class analyzes complex biological processes from the molecular, cellular, extracellular, and organ levels of hierarchy. Emphasis is placed on the basic biochemical and biophysical principles that govern these processes. Examples of processes to be studied include chemotaxis, the fixation of nitrogen into organic biological molecules, growth factor and hormone mediated signaling cascades, and signaling cascades leading to cell death in response to DNA damage. In each case, the availability of a resource, or the presence of a stimulus, results in some biochemical pathways being turned on while others are turned off. The course examines the dynamic aspects of these processes and details how biochemical mechanistic themes impinge on molecular/cellular/tissue/organ-level functions. Chemical and quantitative views of the interplay of multiple pathways as biological networks are emphasized. Student work culminates in the preparation of a unique grant application in an area of biological networks.
This course covers the key quantitative methods of finance: financial econometrics and statistical inference for financial applications; dynamic optimization; Monte Carlo simulation; stochastic (Itô) calculus. These techniques, along with their computer implementation, are covered in depth. Application areas include portfolio management, risk management, derivatives, and proprietary trading.
This course focuses on alternative ways in which the issues of growth, restructuring, innovation, knowledge, learning, and accounting and measurements can be examined, covering both industrialized and emerging countries. We give special emphasis to recent transformations in regional economies throughout the world and to the implications these changes have for the theories and research methods used in spatial economic analyses. Readings will relate mainly to the United States, but we cover pertinent material on foreign countries in lectures.
This course teaches students how to understand the rationality behind how organizations and their programs behave, and to be comfortable and analytical with a live organization. It thereby builds analytic skills for evaluating programs and projects, organizations, and environments. It draws on the literature of the sociology of organizations, political science, public administration, and historical experience-and is based on both developing-country and developed-country experience.
15.875 is a project-based course that explores how organizations can use system dynamics to achieve important goals. In small groups, students learn modeling and consulting skills by working on a term-long project with real-life managers. A diverse set of businesses and organizations sponsor class projects, from start-ups to the Fortune 500. The course focuses on gaining practical insight from the system dynamics process, and appeals to people interested in system dynamics, consulting, or managerial policy-making.
This course covers empirical strategies for applied micro research questions. Our agenda includes regression and matching, instrumental variables, differences-in-differences, regression discontinuity designs, standard errors, and a module consisting of 8–9 lectures on the analysis of high-dimensional data sets a.k.a. "Big Data".
The fact of scarcity forces individuals, firms, and societies to choose among alternative uses – or allocations – of its limited resources. Accordingly, the first part of this summer course seeks to understand how economists model the choice process of individual consumers and firms, and how markets work to coordinate these choices. It also examines how well markets perform this function using the economist's criterion of market efficiency.
Overall, this course focuses on microeconomics, with some topics from macroeconomics and international trade. It emphasizes the integration of theory, data, and judgment in the analysis of corporate decisions and public policy, and in the assessment of changing U.S. and international business environments.