20191 Masters Flashcards
CSCI 501
Numerical Analysis and Computation
Linear equations and matrices, Gauss elimination, error estimates, iteration techniques; contractive mappings, Newton’s method; matrix eigenvalue problems; least-squares approximation, Newton-Cotes and Gaussian quadratures; finite difference methods. Prerequisite: linear algebra and calculus.
CROSSLIST: MATH 501
- Chunming Wang
CSCI 502a
Numerical Analysis
Computational linear algebra; solution of general nonlinear systems of equations; approximation theory using functional analysis; numerical solution of ordinary and partial differential equations.
PREREQ: (MATH 425A and MATH 471)
CROSSLIST: MATH 502a
- Haitian Yue
CSCI 505b
Applied Probability
Markov processes in discrete or continuous time; renewal processes; martingales; brownian motion and diffusion theory; random walks, inventory models, population growth, queuing models, shot noise.
PREREQ: MATH 505A
CROSSLIST: MATH 505b
- Jason Fulman
CSCI 531
Applied Cryptography
Intensive overview of cryptography for practitioners, historical perspective on early systems, number theoretic foundations of modern day cryptosystems and basic cryptanalysis.
CSCI 533
Algebraic Combinatorics
Walks in graphs, random walks, group actions on boolean algebras, Young diagrams and tableaux, the Matrix-Tree Theorem.
CROSSLIST: MATH 533
- Sami Assaf
CSCI 536
Linear Programming and Extensions
Linear programming models for resource allocation; simplex and revised simplex methods; duality; sensitivity; transportation problems; selected extensions to large scale, multiobjective, and special structured models.
PREREQ: 1 from (EE 441 or MATH 225)
CROSSLIST: ISE 536
- Sima Parisay
CSCI 537
Foundations of Data Management
Function and design of modern storage systems, including cloud; data management techniques; data modeling; network attached storage, clusters and data centers; relational databases; the map-reduce paradigm.
CROSSLIST: INF 551
CSCI 545
Robotics
Fundamental skills for modeling and controlling of dynamic systems for robotic applications and graphics animations; control theory; kinematics; dynamics; sensor processing; real-time operating systems; robot labs. Recommended preparation: Basic knowledge in linear algebra (matrices and vectors), calculus, programming in C/C++ or any another language or permission of the instructor.
CSCI 552
Asynchronous VLSI Design
Asynchronous channels and architectures; implementation design styles; controller synthesis; hazards, and races; Petri-nets; performance analysis, and optimization; globally asynchronous locally synchronous design. Open only to graduate students.
PREREQ: EE477
CROSSLIST: EE 552
Registration only for Masters or PhD
- Dan Gunnar Mika Nystroem
CSCI 555L
Advanced Operating Systems
Advanced topics in operating system research: new OS structures, novel memory management, communication, file system, process management, reliability and security techniques.
PREREQ: 1 from (CSCI 350 or CSCI 402)
CSCI 557
Computer Systems Architecture
Computer architecture from a design perspective: Pipelined processors, speculative execution, VLIW, vector processors, GPU/GPGPU, memory technology and systems, interconnection networks, shared-memory and message-passing multiprocessors, chip multiprocessors.
PREREQ: EE 457
CROSSLIST: EE 557
Note: Prerequisite taken at USC or placement exam required
- Michael Dubois
CSCI 559
Mathematical Pattern Recognition
Distribution free classification, discriminant functions, training algorithms; statistical classification, parametric and nonparametric techniques; artificial neural networks.
COREQ: EE 503 and 1 from (EE 441 or EE510)
CROSSLIST: EE 559
- Keith Jenkins
CSCI 561
Foundations of Artificial Intelligence
Foundations of symbolic intelligent systems, search, logic, knowledge representation, planning, learning.
CSCI 567
Machine Learning
Statistical methods for building intelligent and adaptive systems that improve performance from experiences; Focus on theoretical understanding of these methods and their computational implications. Recommended preparation: Undergraduate level training or coursework in linear algebra, multivariate calculus, basic probability and statistics; an undergraduate level course in Artificial Intelligence may be helpful but is not required.
CSCI 570
Analysis of Algorithms
Explores fundamental techniques such as recursion, Fourier transform ordering, dynamic programming for efficient algorithm construction. Examples include arithmetic, algebraic, graph, pattern matching, sorting, searching algorithms.
