EE 376A: Information Theory (STATS 376A)
Projectbased course about how to measure, represent, and communicate information effectively. Why bits have become the universal currency for information exchange. How information theory bears on the design and operation of modernday systems such as smartphones and the Internet. The role of entropy and mutual information in data compression, communication, and inference. Practical compressors and error correcting codes. The information theoretic way of thinking. Relations and applications to probability, statistics, machine learning, biological and artificial neural networks, genomics, quantum information, and blockchains. Prerequisite: a first undergraduate course in probability.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 376B: Topics in Information Theory and Its Applications (STATS 376B)
Information theory establishes the fundamental limits on compression and communication over networks. The tools of information theory have also found applications in many other fields, including probability and statistics, computer science and physics. The course will cover selected topics from these applications, including communication networks, through regular lectures and student projects. Prerequisites:
EE376A
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
Instructors:
El Gamal, A. (PI)
EE 377: Information Theory and Statistics (STATS 311)
Information theoretic techniques in probability and statistics. Fano, Assouad,nand Le Cam methods for optimality guarantees in estimation. Large deviationsnand concentration inequalities (Sanov's theorem, hypothesis testing, thenentropy method, concentration of measure). Approximation of (Bayes) optimalnprocedures, surrogate risks, fdivergences. Penalized estimators and minimumndescription length. Online game playing, gambling, noregret learning. Prerequisites:
EE 376A (or equivalent) or
STATS 300A.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
Instructors:
Duchi, J. (PI)
;
Barnes, L. (TA)
EE 378B: Inference, Estimation, and Information Processing
Techniques and models for signal, data and information processing, with emphasis on incomplete data, nonordered index sets and robust lowcomplexity methods. Linear models; regularization and shrinkage; dimensionality reduction; streaming algorithms; sketching; clustering, search in high dimension; lowrank models; principal component analysis.nnApplications include: positioning from pairwise distances; distributed sensing; measurement/traffic monitoring in networks; finding communities/clusters in networks; recommendation systems; inverse problems. Prerequisites: EE278 and EE263 or equivalent. Recommended but not required:
EE378A
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
Instructors:
Montanari, A. (PI)
;
Chandrasekher, K. (TA)
EE 379: Digital Communication
Modulation: linear, differential and orthogonal methods; signal spaces; power spectra; bandwidth requirements. Detection: maximum likelihood and maximum a posteriori probability principles; sufficient statistics; correlation and matchedfilter receivers; coherent, differentially coherent and noncoherent methods; error probabilities; comparison of modulation and detection methods. Intersymbol interference: singlecarrier channel model; Nyquist requirement; whitened matched filter; maximum likelihood sequence detection; Viterbi algorithm; linear equalization; decisionfeedback equalization. Multicarrier modulation: orthogonal frequencydivision multiplexing; capacity of parallel Gaussian channels; comparison of single and multicarrier techniques. Prerequisite: EE102B and
EE278 (or equivalents). EE279 is helpful but not required.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
Instructors:
Kahn, J. (PI)
EE 380: Colloquium on Computer Systems
Live presentations of current research in the design, implementation, analysis, and applications of computer systems. Topics range over a wide range and are different every quarter. Topics may include fundamental science, mathematics, cryptography, device physics, integrated circuits, computer architecture, programming, programming languages, optimization, applications, simulation, graphics, social implications, venture capital, patent and copyright law, networks, computer security, and other topics of related to computer systems. May be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 1

Repeatable for credit

Grading: Satisfactory/No Credit
Instructors:
Allison, D. (PI)
;
Freeman, A. (PI)
EE 382A: Parallel Processors Beyond Multicore Processing
Formerly
EE392Q. The current parallel computing research emphasizes multicores, but there are alternative array processors with significant potential. This handson course focuses on SIMD (SingleInstruction, MultipleData) massively parallel processors. Topics: Flynn's Taxonomy, parallel architectures, Kestrel architecture and simulator, principles of SIMD programming, parallel sorting with sorting networks, string comparison with dynamic programming (edit distance, SmithWaterman), arbitraryprecision operations with fixedpoint numbers, reductions, vector and matrix multiplication, image processing algorithms, asynchronous algorithms on SIMD ("SIMD Phase Programming Model"), Mandelbrot set, analysis of parallel performance.
Terms: Spr

Units: 3

Grading: Letter (ABCD/NP)
Instructors:
Di Blas, A. (PI)
;
Oliver, L. (TA)
EE 384A: Internet Routing Protocols and Standards
Local area networks addressing and switching; IEEE 802.1 bridging protocols (transparent bridging, virtual LANs). Internet routing protocols: interior gateways (RIP, OSPF) and exterior gateways (BGP); multicast routing; multiprotocol label switching (MPLS). Routing in mobile networks: Mobile IP, Mobile Ad Hoc Networks (MANET), Wireless Mesh Networks. Prerequisite:
EE 284 or
CS 144.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
Instructors:
Tobagi, F. (PI)
EE 384S: Performance Engineering of Computer Systems & Networks
Modeling and control methodologies for highperformance network engineering, including: Markov chains and stochastic modeling, queueing networks and congestion management, dynamic programming and task/processor scheduling, network dimensioning and optimization, and simulation methods. Applications for design of highperformance architectures for wireline/wireless networks and the Internet, including: traffic modeling, admission and congestion control, quality of service support, power control in wireless networks, packet scheduling in switches, video streaming over wireless links, and virus/worm propagation dynamics and countermeasures. Enrollment limited to 30. Prerequisites: basic networking technologies and probability.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
Instructors:
Bambos, N. (PI)
EE 385A: Robust and Testable Systems Seminar
Student/faculty discussions of research problems in the design of reliable digital systems. Areas: faulttolerant systems, design for testability, production testing, and system reliability. Emphasis is on student presentations and Ph.D. thesis research. May be repeated for credit. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr

Units: 14

Repeatable for credit

Grading: Letter or Credit/No Credit
Instructors:
Mitra, S. (PI)
Filter Results: