Winter 2016 Course Timetable. Legend: TIME: M = Monday T = Tuesday W = Wednesday R = Thursday F = Friday BREATH: M = Methodology: RA = Research Area

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1 Winter 2016 Course Timetable Legend: TIME: M = Monday T = Tuesday W = Wednesday R = Thursday F = Friday BREATH: M = Methodology: RA = Research Area Please note: Times listed in parentheses refer to the tutorial meeting times. Course numbers in parentheses indicate the undergraduate section of a cross-listed course. Course ID Section Course Title & Description Instructor Time Location Breadth CSC2511H (401) Natural Language Computing Introduction to techniques involving natural language and speech in applications such as information retrieval, extraction, and filtering; intelligent Web searching; spelling and grammar checking; speech recognition and synthesis; and multi-lingual systems including machine translation. N-grams, POS-tagging, semantic distance metrics, indexing, online lexicons and thesauri, markup languages, collections of on-line documents, corpus analysis. Python software F. Rudzicz MWF (F10) OI G162 RA4/M2 CSC2506H Uncertainty & Learning (412) Representing uncertain knowledge using probability and other formalisms. Qualitative and quantitative specification of probability distributions using graphical models. Algorithms for inference with graphical models. Statistical approaches and algorithms for learning models from experience. Examples will be given of applications of these models in various areas of artificial intelligence. R. Zemel T3-5 (R1) MP137 R12/M1 CSC2504H (418) L5101 Computer Graphics Identification and characterization of the objects manipulated in computer graphics, the operations possible on these objects, efficient algorithms to perform these operations, and interfaces to transform one type of object to another. Display devices, display data structures and procedures, graphical input, object modeling, transformations, illumination models, primary and secondary light effects; graphics packages and systems. K. Singh W3-5 (M3) T7-9 (T6) SS1085 MP137 RA5/M2

2 Course ID Section Course Title & Description Instructor Time Location Breadth CSC2514H (428) Human-Computer Interaction CSC428H/2514 is the department's second course in Human Computer Interaction. It builds on the department's first course in HCI, CSC318, and what students learned there about interface design through task analysis, usability testing and iterative design. While the focus in 318 was largely on the design process, this second course will focus more on the underlying models of human-computer interaction, rigorous evaluation, and research frontiers. Topics to be discusses include, but are not limited to: Models of HCI from the human and device perspectives; Evaluation methodologies; Experimental Design; Analysis techniques; State-of-the-art and future user interfaces; Research directions. O.St Cyr M7-9 (M6) BA1220 RA10/M4 CSC2527H (454) The Business of Software The focus of the course is the key factors involved in hypothesising, validating and executing a viable business model necessary to launch and sustain a successful software-based business venture. In the course, you will learn techniques and methodologies that will give you a distinct career advantage after graduation. It is designed to give you a true-to-life experience of the thought process behind successful business ventures, whether you plan on creating your own startup or working for an established employer. In either case, critical business analysis skills complement the computer science skills sought by the industry. M.Grech & H.Kontozopoulos W6-8 (W8) BA1210 RA10/M4 CSC2600H *(454) Capstone Design Project M.Grech & J.Foster T6-9 (W8) BA1210 CSC2305H (466) Numerical Methods for Optimization Possible topics include: optimization along a line; steepest descent methods; Newton's method; quasi-newton methods; conjugate gradient methods; variants of Newton's method for nonlinear least squares problems; projection methods for optimization subject to linear constraints; Lagrangian methods for optimization subject to nonlinear equality constraints; penalty function methods for optimization subject to nonlinear inequality constraints. Possible Preparatory Reading: The student should be familiar with Newton's method for systems of nonlinear equations as well as Gaussian elimination for systems of linear equations. T. Fairgrieve MWF 1-2 SS1072 RA13/M2

3 Course ID Section Course Title & Description Instructor Time Location Breadth CSC2502H (486) Knowledge Representation & Reasoning Representing knowledge symbolically in a form suitable for automated reasoning, and associated reasoning methods: first-order logic, entailment, the resolution method, Horn clauses, description logics, probabilities, tractable reasoning, the representation of action, and planning, among other topics. F12-2 (W1) LM157 RA11/M1 CSC2107H (488) Compilers & Interpreters Compiler organization, compiler writing tools, use of regular expressions, finite automata and context-free grammars, scanning and parsing, runtime organization, semantic analysis, implementing the runtime model, storage allocation, code generation. Prerequisite: Courses in data structures and programming languages. Solid knowledge of Java. TR2-3 (R1) SS2106 RA14/M3 CSC2208H (469) Operating Systems Design Principles of operating systems. The operating system as a control program and as a resource allocator. The concept of a process will be central: synchronization, mutual exclusion, and deadlock. Additional topics include memory management, file systems, process scheduling, and protection. Some treatment of multiprocessor issues, such as threads and scheduling. Case studies from systems such as Unix and Mach. Experimentation with a simple operating system using a concurrent programming language. CSC2420H Algorithm Design Analysis & Theory This course is a graduate level introduction to the design and analysis of algorithms. The course is a foundational course, appropriate for students in computer science, computer engineering, and mathematics. We will begin with topics normally discussed in undergraduate courses such as CSC373 (Algorithm Design, Analysis & Complexity) or CSC375 (Enriched Algorithm Design, Analysis, and Complexity) using some less standard examples and also discussing some precise models for standard algorithmic paradigms such as greedy, local search and dynamic programming algorithms. Other possible topics include: randomized algorithms and Markov chains, LP and SDP relaxations, primal dual algorithms, online primal dual algorithms, multi commodity flows, embedding techniques, data stream algorithms, sub-linear time algorithms, multiplicative weights algorithms, spectral methods; we will B.Simion TR10 (F3) SS2127 M3 A. Borodin R2-4 BA2135 RA1/M1

4 discuss applications to areas such as mechanism design, social networks, wireless networks, and information retrieval. Course ID Section Course Title & Description Instructor Time Location Breadth CSC2523H Object Modeling and Recognition: Deep Learning in Computer Vision This class is a graduate seminar course in computer vision. The class will focus on the topic of visual recognition by exploiting textual information. We will discuss various problems and applications in this domain, and survey the current papers on the topic of images/videos and text. The goal of the class will be to understand the cross-domain approaches, to analyze their strengths and weaknesses, as well as to identify interesting new directions for future research. Prerequisites: Courses in computer vision and/or machine learning (e.g., CSC320, CSC420) are highly recommended (otherwise you will need some additional reading), and basic programming skills are required for projects. S.Fidler W 11-1 BA2135 RA7/M1 CSC2720H Systems Thinking for Global Problems The dynamics of global change are complex, and demand new ways of conceptualizing and analyzing complex adaptive systems and their interrelationships. In this course, we apply systems thinking as a conceptual toolkit for studying the relationships between challenges such as globalization, climate change, energy, health & wellbeing, and food security. The course will use a series of systems thinking games to explore ideas from General Systems Theory, Cybernetics, Systems Dynamics Modeling, Complexity Science, Earth System Modeling, Soft Systems Methods, and Critical System Theory. We will explore relationships between concepts such as resilience, sustainability, feedback loops, limits to growth, tipping points, chaos and boundary critique. The course is open to students from any discipline, and we actively seek a diverse set of students, from many backgrounds to provide multiple perspectives. There are no prerequisites. S. Easterbrook M 2-5 BA2195 RA15/M4 Exclusion: CSC2602 and DGC 2003 CSC2415H Advanced Topics in Distributed Computing A seminar-style, project-oriented course exploring recent and current research in distributed computing. Prerequisite: CSC2221 or permission of the instructor. S.Toueg/ V.Hadzilacos F 1-4 HS100 RA9/M1

5 CSC2431H Topics in Computational Biology: Using Computation for Medicine In this seminar class we will discuss the user of various Computer Science methodologies in diverse medical fields. This will include methodologies from Algorithms, Machine Learning, Vision, Human-Computer Interaction, and Data Visualization to medical genomics, electronic medical records, surgery, and others. Each class meeting will include student presentations as well as presentations and discussion from scientists and medical experts. M.Brudno F10-12 RS310 M4/RA3 CSC2541H Topics in Machine Learning: Visual Perception for Autonomous Driving This class is a graduate course in visual perception for autonomous driving. The class will briefly cover topics in localization, ego-motion estimation, freespace estimation, visual recognition (classification, detection, segmentation), etc R.Urtasun T1-3 BA2145 M2/RA12 Prerequisites: A good knowledge of statistics, linear algebra, calculus is necessary as well as good programming skills. A good knowledge of computer vision and machine learning is strongly recommended. *Students enrolled on CSC2600H should also enrol on CSC2527H.

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